ABSTRACT In this paper, a Dynamic Stochastic Resonance (DSR)-based watermark extraction technique... more ABSTRACT In this paper, a Dynamic Stochastic Resonance (DSR)-based watermark extraction technique in discrete cosine transform (DCT) domain has been presented for copyright protection of audio signals. Watermark as a logo is embedded into the most prominent peaks of the highest energy segment of the audio DCT coefficients. DSR has been used to improve the robustness of the extraction algorithm by utilizing the degradation that introduces during various signal processing and geometrical attacks. Tuning of the DCT coefficients of the watermarked signal by noise-induced resonance improves the authenticity of the watermarked signal. DSR is an iterative process due to which the effect of noise is suppressed and hidden information is enhanced. Response of the proposed extraction scheme suggests increased robustness against various attacks such as noise addition, cropping, re-sampling, re-quantization, MP3 compression, and echo without trading-off with visual quality of the watermarked logo. Comparison with the existing DCT, DWT, and SVD techniques shows the better performance in terms of correlation coefficient and visual quality of extracted watermark.
Journal of Visual Communication and Image Representation, 2021
Abstract A usual problem encountered during bad weather conditions is the degraded image quality ... more Abstract A usual problem encountered during bad weather conditions is the degraded image quality due to haze/fog. In basic Gamma correction method there is always an uncertainty regarding the choice of a particular exponential factor, which improves the quality of the input image because of the nonlinearity involved in the process. This issue has been solved in this study by proposing a modified Gamma correction method, in which the exponential correction factor is varied incrementally to generate images. We also propose the implementation of an automatic image selection criterion for fusion which helps chose images with varied and distinct features. The implementation of the multi-exposure fusion framework is done in the hue-saturation-value color space which has close resemblance with the human vision. The intensity channel of the selected images is fused in the gradient domain which captures minute details and takes an edge as compared to other conventional fusion based methods. The fused saturation channel is obtained by averaging fusion followed by enhancement using a non-linear sigmoid function. The hue channel of the input hazy image is left unprocessed to avoid color distortion. The experimental analysis demonstrates that the proposed method outperforms most of the single image dehazing methods.
This paper presents an algorithm for noise removal from digital image, based on stochastic noise ... more This paper presents an algorithm for noise removal from digital image, based on stochastic noise pattern. We apply white Gaussian noise to improve the quality of the noisy input image to get the de-noised response image. Input noisy image is subjected to independent additive white Gaussian noise of different standard deviation, the output image corresponding to individual noise standard deviation, summed and averaged, to get the denoised image. This behavior is termed as “Suprathreshold Stochastic Resonance ” (SSR) [1]. We have shown that SSR occurs for image de-noising. Here, threshold is taken as the mean of the noise added input noisy image. Generally, threshold phenomenon plays a major role in stochastic resonance (SR) and supra-threshold stochastic resonance (SSR). Depending on the threshold value, non-dynamical SR or SSR condition can be set up. The results of these are quantified appropriately through visualization of an output image and through the plot of PSNR. Key issue of...
Fourth International Conference on Information, Communications and Signal Processing, 2003 and the Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint
Wavelets for Content Based Image Retrieval and Digital Watermarking for Multimedia Applications .... more Wavelets for Content Based Image Retrieval and Digital Watermarking for Multimedia Applications ... BN Chatterji, Manesh Kokare, A. Adhipathi Reddy, Rajib Kumar Jha ... Electronics and Electrical Communication Engineering Department, Indian Institute of Technology, Kharagpur -721 ...
The Radon transform is an important transform to detect line feature from the noisy image. Radon ... more The Radon transform is an important transform to detect line feature from the noisy image. Radon transform can transform two-dimensional images (with noisy or disturbed lines) into a domain of possible parameters of line, where each line in the image will give a peak position at the corresponding parameters of the line. It has led to many line detection applications within image processing, computer vision, earthquake engineering etc. When the lines are subjected to very high background noises, Radon transform alone is not so effective. Here, in this paper, we propose dynamic stochastic resonance (DSR) based Radon transform for weak line extraction. The DSR is an iterative process that tunes the coefficient of Radon transform so that we may get the enhanced lines of the image. We compare our proposed method with the results of the Gaussian low pass filter. The proposed technique adopts local adaptive processing, and it significantly enhances the line feature of an image. Experimenta...
2016 Sixth International Symposium on Embedded Computing and System Design (ISED), 2016
The visibility of the underwater images is highly affected by two major sources of distortion i.e... more The visibility of the underwater images is highly affected by two major sources of distortion i.e., light scattering and colour change. The multiple reflection and deflection by particles present in the water cause a decrement in visibility and contrast of the image captured by the camera. Distinct attenuation in different component of colour (R, G, B) consequences the colour change in the image. In this paper, a novel systematic approach based on a fractional filter has been used to enhance the low contrast underwater image. The order of the fractional derivative has been chosen adaptively, which largely depends on the presence of the weak and strong edges. Depending upon the amount of attenuation to each light wavelength, the colour change is compensated in order to restore the colour information. The results obtained demonstrate that there is a significant improvement in visibility and colour fidelity. The result has been compared with some state-of-the-art technique and it is observed that the results obtained are at most comparable to the existing technique.
This paper presents an algorithm for noise removal from digital image, based on stochastic noise ... more This paper presents an algorithm for noise removal from digital image, based on stochastic noise pattern. We apply white Gaussian noise to improve the quality of the noisy input image to get the de -noised response image. Input noisy image is subjected to independent additive white Gaussian noise of different standard deviation, the output image corresponding to individual noise standard
Use of stochastic resonance for image application is a very challenging task. This thesis present... more Use of stochastic resonance for image application is a very challenging task. This thesis presents novel techniques for image enhancement, segmentation and watermark detection using stochastic resonance. The mathematical foundation of stochastic resonance for image enhancement has been presented here. Two stochastic resonance (SR) based methods are introduced for enhancement of very low contrast images. The novel SR based techniques enhance the information without introducing any artifacts and spots in the images. SR is a phenomenon wherein addition of random noise of optimum intensity to a week noisy signal and passing through a non-linearity enhances output signal-to-noise ratio (SNR). This was first reported by Benzi et al. [10]. Nonlinearity is taken as hard thresholding operation. Output (SNR) depends upon threshold Δ and noise standard deviation σ. In the proposed SR based image enhancement technique-1, an expression for optimum threshold has been derived. Gaussian noise of in...
2018 8th International Symposium on Embedded Computing and System Design (ISED), 2018
The security of the digital images plays a key role in defence and biomedical image processing ap... more The security of the digital images plays a key role in defence and biomedical image processing applications. The algorithm which is to be used for the security of data provides robustness from any inaccurate delivery to the unauthorized user. The concept of share matrix $S_{m}^{(k,n)}$ for the generation of shares has been explored. These shares provide a backbone to the encryption or security of the confidential data/images.Here, this paper demonstrates the use of share generation concept for encryption of the digital images in the singular value decomposition (SVD) domain. The singular value of the SVD component acts as the right choice to generate the shares of the image. For further enhancement in the robustness, we apply fractional Fourier transform (FrFT). The order of the FrFT ($\alpha _{1},\,\alpha _{2}$) along with the singular vectors (i.e., ${U}$ and ${V}$) components of the original image works as keys.The state-of-the-art techniques have also been studied along with the...
2017 International Conference on Noise and Fluctuations (ICNF), 2017
In this paper, we have investigated a novel stochastic resonance & particle swarm optimization (P... more In this paper, we have investigated a novel stochastic resonance & particle swarm optimization (PSO) technique for weak signal detection from noisy signal (weak signal + internal noise). PSO technique is used to determine the optimal amount of noise for weak signal detection. Our proposed work is in Neyman-Pearson framework which maximizes the probability of detection PD for a fixed value of probability of false alarm PFA. With the equality and in-equality constraints, we have explored the penalty function method to design unconstrained objective function. In the proposed technique, we have considered 2 different, 3 different and 4 different noises separately and observed that the probability of detection PD gets increased. Simulations are performed to investigate the result with a numerical example to exhibit the practicality of the proposed technique.
In this paper, a non-linear non-dynamic stochastic resonance (SR) based technique is proposed for... more In this paper, a non-linear non-dynamic stochastic resonance (SR) based technique is proposed for enhancement of dark and low contrast images. Noise-enhanced signal processing theory is applied to a low contrast image to improve the contrast. Insufficient illumination is the major cause of low contrast of the image, which can be stated as internal noise. This internal noise is neutralized by the addition of some pre-calculated external noise. The low contrast image is added to different frames of random noise and is thresholded repeatedly against a fixed parameter. After that, averaging produces a high contrast (enhanced) image. Noise-induced resonance is obtained at a particular optimum noise intensity. This optimum intensity is obtained by varying the noise intensities. Performance of the proposed technique is investigated for Gaussian noise. Quantitative evaluation of the performance is done in terms of color enhancement, contrast enhancement factor, and perceptual quality measur...
Noise plays a constructive role in a lot of non-linear applications. Many non-linear systems perf... more Noise plays a constructive role in a lot of non-linear applications. Many non-linear systems perform better when some calculated external noise is added. This phenomenon is called stochastic resonance (SR). When a parallel array of SR is used, it is termed as Suprathreshold Stochastic Resonance (SSR). Many of the systems and models where SR is effectively observed are non-linear systems with a single threshold value. In the existing literature, the effect of SSR with respect to various noises such as Gaussian noise, Uniform noise etc. has been studied [1], [2]. The expression for cross-correlation has also been derived in terms of number of parallel arrays, the variance of the input signal and the variance of the external noise which is added. In this paper, the effect of SSR using Gamma noise has been reported and the expression for cross-correlation has been derived. Furthermore, the same concept has been used in a watermarking application, where Gamma noise is added as a signatur...
The detection of a weak signal from noisy data is an important task in many signal processing app... more The detection of a weak signal from noisy data is an important task in many signal processing applications such as radar communication, biomedical engineering etc. However, the amplitude of the known signal plays a big role in terms of complexity and performance of the detector. In other words, detection of the weak signal is a big challenge. Here, we investigate approximated fractional integrator (AFI) based detector. The proposed method has been employed for detection of DC signal which is present in the Gaussian noise. Our proposed method has been compared with some state-of-the-art methods in terms of probability of detection $(P_{D})$ for a constant value of probability of false alarm $(P_{FA})$. The $P_{D}$ has been plotted for varying signal-to-noise ratio (SNR) at a constant value of $P_{FA}$. Furthermore, we apply the proposed method for watermark application. The outcomes of the proposed method are convincing and it suggests that the proposed method works better or compara...
In this paper, new image encryption based on singular value decomposition (SVD), fractional discr... more In this paper, new image encryption based on singular value decomposition (SVD), fractional discrete cosine transform (FrDCT) and the chaotic system is proposed for the security of medical image. Reliability, vitality, and efficacy of medical image encryption are strengthened by it. The proposed method discusses the benefits of FrDCT over fractional Fourier transform. The key sensitivity of the proposed algorithm for different medical images inspires us to make a platform for other researchers. Theoretical and statistical tests are carried out demonstrating the high-level security of the proposed algorithm.
This paper proposes a novel approach for image watermarking using combined dynamic stochastic res... more This paper proposes a novel approach for image watermarking using combined dynamic stochastic resonance (DSR) and support vector machine (SVM). The algorithm incorporates lifting wavelet transform (LWT) to decompose the host image into three level frequency sub-bands, and a low-pass frequency sub-band is opted for watermark embedding. Watermark bits are embedded into small blocks of low-pass frequency sub-band using quantization of minimum and maximum coefficients of the corresponding blocks. And, to extract the watermark, DSR based coefficient enhancement process is incorporated. A features set of enhanced block coefficients is generated by employing different statistical parameters, and principal component analysis (PCA) is employed to reduce the dimensions of the features set, which are used for training and testing the learning machine. Training and testing patterns are generated using concatenation of reduced features with enhanced coefficients of the corresponding blocks. Fina...
ABSTRACT In this paper, a Dynamic Stochastic Resonance (DSR)-based watermark extraction technique... more ABSTRACT In this paper, a Dynamic Stochastic Resonance (DSR)-based watermark extraction technique in discrete cosine transform (DCT) domain has been presented for copyright protection of audio signals. Watermark as a logo is embedded into the most prominent peaks of the highest energy segment of the audio DCT coefficients. DSR has been used to improve the robustness of the extraction algorithm by utilizing the degradation that introduces during various signal processing and geometrical attacks. Tuning of the DCT coefficients of the watermarked signal by noise-induced resonance improves the authenticity of the watermarked signal. DSR is an iterative process due to which the effect of noise is suppressed and hidden information is enhanced. Response of the proposed extraction scheme suggests increased robustness against various attacks such as noise addition, cropping, re-sampling, re-quantization, MP3 compression, and echo without trading-off with visual quality of the watermarked logo. Comparison with the existing DCT, DWT, and SVD techniques shows the better performance in terms of correlation coefficient and visual quality of extracted watermark.
Journal of Visual Communication and Image Representation, 2021
Abstract A usual problem encountered during bad weather conditions is the degraded image quality ... more Abstract A usual problem encountered during bad weather conditions is the degraded image quality due to haze/fog. In basic Gamma correction method there is always an uncertainty regarding the choice of a particular exponential factor, which improves the quality of the input image because of the nonlinearity involved in the process. This issue has been solved in this study by proposing a modified Gamma correction method, in which the exponential correction factor is varied incrementally to generate images. We also propose the implementation of an automatic image selection criterion for fusion which helps chose images with varied and distinct features. The implementation of the multi-exposure fusion framework is done in the hue-saturation-value color space which has close resemblance with the human vision. The intensity channel of the selected images is fused in the gradient domain which captures minute details and takes an edge as compared to other conventional fusion based methods. The fused saturation channel is obtained by averaging fusion followed by enhancement using a non-linear sigmoid function. The hue channel of the input hazy image is left unprocessed to avoid color distortion. The experimental analysis demonstrates that the proposed method outperforms most of the single image dehazing methods.
This paper presents an algorithm for noise removal from digital image, based on stochastic noise ... more This paper presents an algorithm for noise removal from digital image, based on stochastic noise pattern. We apply white Gaussian noise to improve the quality of the noisy input image to get the de-noised response image. Input noisy image is subjected to independent additive white Gaussian noise of different standard deviation, the output image corresponding to individual noise standard deviation, summed and averaged, to get the denoised image. This behavior is termed as “Suprathreshold Stochastic Resonance ” (SSR) [1]. We have shown that SSR occurs for image de-noising. Here, threshold is taken as the mean of the noise added input noisy image. Generally, threshold phenomenon plays a major role in stochastic resonance (SR) and supra-threshold stochastic resonance (SSR). Depending on the threshold value, non-dynamical SR or SSR condition can be set up. The results of these are quantified appropriately through visualization of an output image and through the plot of PSNR. Key issue of...
Fourth International Conference on Information, Communications and Signal Processing, 2003 and the Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint
Wavelets for Content Based Image Retrieval and Digital Watermarking for Multimedia Applications .... more Wavelets for Content Based Image Retrieval and Digital Watermarking for Multimedia Applications ... BN Chatterji, Manesh Kokare, A. Adhipathi Reddy, Rajib Kumar Jha ... Electronics and Electrical Communication Engineering Department, Indian Institute of Technology, Kharagpur -721 ...
The Radon transform is an important transform to detect line feature from the noisy image. Radon ... more The Radon transform is an important transform to detect line feature from the noisy image. Radon transform can transform two-dimensional images (with noisy or disturbed lines) into a domain of possible parameters of line, where each line in the image will give a peak position at the corresponding parameters of the line. It has led to many line detection applications within image processing, computer vision, earthquake engineering etc. When the lines are subjected to very high background noises, Radon transform alone is not so effective. Here, in this paper, we propose dynamic stochastic resonance (DSR) based Radon transform for weak line extraction. The DSR is an iterative process that tunes the coefficient of Radon transform so that we may get the enhanced lines of the image. We compare our proposed method with the results of the Gaussian low pass filter. The proposed technique adopts local adaptive processing, and it significantly enhances the line feature of an image. Experimenta...
2016 Sixth International Symposium on Embedded Computing and System Design (ISED), 2016
The visibility of the underwater images is highly affected by two major sources of distortion i.e... more The visibility of the underwater images is highly affected by two major sources of distortion i.e., light scattering and colour change. The multiple reflection and deflection by particles present in the water cause a decrement in visibility and contrast of the image captured by the camera. Distinct attenuation in different component of colour (R, G, B) consequences the colour change in the image. In this paper, a novel systematic approach based on a fractional filter has been used to enhance the low contrast underwater image. The order of the fractional derivative has been chosen adaptively, which largely depends on the presence of the weak and strong edges. Depending upon the amount of attenuation to each light wavelength, the colour change is compensated in order to restore the colour information. The results obtained demonstrate that there is a significant improvement in visibility and colour fidelity. The result has been compared with some state-of-the-art technique and it is observed that the results obtained are at most comparable to the existing technique.
This paper presents an algorithm for noise removal from digital image, based on stochastic noise ... more This paper presents an algorithm for noise removal from digital image, based on stochastic noise pattern. We apply white Gaussian noise to improve the quality of the noisy input image to get the de -noised response image. Input noisy image is subjected to independent additive white Gaussian noise of different standard deviation, the output image corresponding to individual noise standard
Use of stochastic resonance for image application is a very challenging task. This thesis present... more Use of stochastic resonance for image application is a very challenging task. This thesis presents novel techniques for image enhancement, segmentation and watermark detection using stochastic resonance. The mathematical foundation of stochastic resonance for image enhancement has been presented here. Two stochastic resonance (SR) based methods are introduced for enhancement of very low contrast images. The novel SR based techniques enhance the information without introducing any artifacts and spots in the images. SR is a phenomenon wherein addition of random noise of optimum intensity to a week noisy signal and passing through a non-linearity enhances output signal-to-noise ratio (SNR). This was first reported by Benzi et al. [10]. Nonlinearity is taken as hard thresholding operation. Output (SNR) depends upon threshold Δ and noise standard deviation σ. In the proposed SR based image enhancement technique-1, an expression for optimum threshold has been derived. Gaussian noise of in...
2018 8th International Symposium on Embedded Computing and System Design (ISED), 2018
The security of the digital images plays a key role in defence and biomedical image processing ap... more The security of the digital images plays a key role in defence and biomedical image processing applications. The algorithm which is to be used for the security of data provides robustness from any inaccurate delivery to the unauthorized user. The concept of share matrix $S_{m}^{(k,n)}$ for the generation of shares has been explored. These shares provide a backbone to the encryption or security of the confidential data/images.Here, this paper demonstrates the use of share generation concept for encryption of the digital images in the singular value decomposition (SVD) domain. The singular value of the SVD component acts as the right choice to generate the shares of the image. For further enhancement in the robustness, we apply fractional Fourier transform (FrFT). The order of the FrFT ($\alpha _{1},\,\alpha _{2}$) along with the singular vectors (i.e., ${U}$ and ${V}$) components of the original image works as keys.The state-of-the-art techniques have also been studied along with the...
2017 International Conference on Noise and Fluctuations (ICNF), 2017
In this paper, we have investigated a novel stochastic resonance & particle swarm optimization (P... more In this paper, we have investigated a novel stochastic resonance & particle swarm optimization (PSO) technique for weak signal detection from noisy signal (weak signal + internal noise). PSO technique is used to determine the optimal amount of noise for weak signal detection. Our proposed work is in Neyman-Pearson framework which maximizes the probability of detection PD for a fixed value of probability of false alarm PFA. With the equality and in-equality constraints, we have explored the penalty function method to design unconstrained objective function. In the proposed technique, we have considered 2 different, 3 different and 4 different noises separately and observed that the probability of detection PD gets increased. Simulations are performed to investigate the result with a numerical example to exhibit the practicality of the proposed technique.
In this paper, a non-linear non-dynamic stochastic resonance (SR) based technique is proposed for... more In this paper, a non-linear non-dynamic stochastic resonance (SR) based technique is proposed for enhancement of dark and low contrast images. Noise-enhanced signal processing theory is applied to a low contrast image to improve the contrast. Insufficient illumination is the major cause of low contrast of the image, which can be stated as internal noise. This internal noise is neutralized by the addition of some pre-calculated external noise. The low contrast image is added to different frames of random noise and is thresholded repeatedly against a fixed parameter. After that, averaging produces a high contrast (enhanced) image. Noise-induced resonance is obtained at a particular optimum noise intensity. This optimum intensity is obtained by varying the noise intensities. Performance of the proposed technique is investigated for Gaussian noise. Quantitative evaluation of the performance is done in terms of color enhancement, contrast enhancement factor, and perceptual quality measur...
Noise plays a constructive role in a lot of non-linear applications. Many non-linear systems perf... more Noise plays a constructive role in a lot of non-linear applications. Many non-linear systems perform better when some calculated external noise is added. This phenomenon is called stochastic resonance (SR). When a parallel array of SR is used, it is termed as Suprathreshold Stochastic Resonance (SSR). Many of the systems and models where SR is effectively observed are non-linear systems with a single threshold value. In the existing literature, the effect of SSR with respect to various noises such as Gaussian noise, Uniform noise etc. has been studied [1], [2]. The expression for cross-correlation has also been derived in terms of number of parallel arrays, the variance of the input signal and the variance of the external noise which is added. In this paper, the effect of SSR using Gamma noise has been reported and the expression for cross-correlation has been derived. Furthermore, the same concept has been used in a watermarking application, where Gamma noise is added as a signatur...
The detection of a weak signal from noisy data is an important task in many signal processing app... more The detection of a weak signal from noisy data is an important task in many signal processing applications such as radar communication, biomedical engineering etc. However, the amplitude of the known signal plays a big role in terms of complexity and performance of the detector. In other words, detection of the weak signal is a big challenge. Here, we investigate approximated fractional integrator (AFI) based detector. The proposed method has been employed for detection of DC signal which is present in the Gaussian noise. Our proposed method has been compared with some state-of-the-art methods in terms of probability of detection $(P_{D})$ for a constant value of probability of false alarm $(P_{FA})$. The $P_{D}$ has been plotted for varying signal-to-noise ratio (SNR) at a constant value of $P_{FA}$. Furthermore, we apply the proposed method for watermark application. The outcomes of the proposed method are convincing and it suggests that the proposed method works better or compara...
In this paper, new image encryption based on singular value decomposition (SVD), fractional discr... more In this paper, new image encryption based on singular value decomposition (SVD), fractional discrete cosine transform (FrDCT) and the chaotic system is proposed for the security of medical image. Reliability, vitality, and efficacy of medical image encryption are strengthened by it. The proposed method discusses the benefits of FrDCT over fractional Fourier transform. The key sensitivity of the proposed algorithm for different medical images inspires us to make a platform for other researchers. Theoretical and statistical tests are carried out demonstrating the high-level security of the proposed algorithm.
This paper proposes a novel approach for image watermarking using combined dynamic stochastic res... more This paper proposes a novel approach for image watermarking using combined dynamic stochastic resonance (DSR) and support vector machine (SVM). The algorithm incorporates lifting wavelet transform (LWT) to decompose the host image into three level frequency sub-bands, and a low-pass frequency sub-band is opted for watermark embedding. Watermark bits are embedded into small blocks of low-pass frequency sub-band using quantization of minimum and maximum coefficients of the corresponding blocks. And, to extract the watermark, DSR based coefficient enhancement process is incorporated. A features set of enhanced block coefficients is generated by employing different statistical parameters, and principal component analysis (PCA) is employed to reduce the dimensions of the features set, which are used for training and testing the learning machine. Training and testing patterns are generated using concatenation of reduced features with enhanced coefficients of the corresponding blocks. Fina...
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Papers by Rajib Kumar Jha