ICST Transactions on Scalable Information Systems, 2022
INTRODUCTION: In image processing noise removal is a hot research field. Lots of studies have bee... more INTRODUCTION: In image processing noise removal is a hot research field. Lots of studies have been carried out and
many algorithms and filters have been planned to improve the image information. There are various noise removal
procedures to identify and remove the corrupted pixels. But several image de-noising algorithms apply the filter to the
overall image to filter non-corrupted pixels also. To overcome these weaknesses, we proposed an efficient denoising
algorithm by cascading Adaptive Median Filter (AMF) with Modified Decision Based Median Filter (MDBMF).
OBJECTIVES: To acquire an efficient denoising algorithm for impulse noise reduction by combining AMF and MDBMF
methods which are effective, efficient for denoising various kinds of images.
To retain the edges, prevent signal deterioration, and ensure non-corrupted image pixels are remaining intact, regardless of
various degrees of noise in the image.
To avoid the condition where noisy pixels are replaced by other noisy pixels to maintain the quality of images from its
degraded noise version such as blur which often takes place during transmission, acquisition, storage, etc.
METHODS, RESULTS AND CONCLUSION: The performance corroboration of the proposed efficient denoising
algorithmis accomplished employing nine standard grayscale images. The size of all standard images kept 256x256 pixels
in this research. The proposed image denoising system has experimented on those images affected with 10% to 90% salt &
pepper noise density. Additionally, the performance of the existing state-of-art denoising techniques like AMF, MF, WMF,
UMF, and DBMF are contrasted with the proposed hybrid approach. The results showed that de-noised images obtained
for 10% to 90% densities levels by proposed hybrid approach are quite better than the quality of denoised images achieved
from WMF, UTMF, AMF, and DBMF methods. The proposed algorithm effectively eradicates salt and pepper noise for
lower to higher image noise densities levels.
ICST Transactions on Scalable Information Systems, 2022
INTRODUCTION: In image processing noise removal is a hot research field. Lots of studies have bee... more INTRODUCTION: In image processing noise removal is a hot research field. Lots of studies have been carried out and
many algorithms and filters have been planned to improve the image information. There are various noise removal
procedures to identify and remove the corrupted pixels. But several image de-noising algorithms apply the filter to the
overall image to filter non-corrupted pixels also. To overcome these weaknesses, we proposed an efficient denoising
algorithm by cascading Adaptive Median Filter (AMF) with Modified Decision Based Median Filter (MDBMF).
OBJECTIVES: To acquire an efficient denoising algorithm for impulse noise reduction by combining AMF and MDBMF
methods which are effective, efficient for denoising various kinds of images.
To retain the edges, prevent signal deterioration, and ensure non-corrupted image pixels are remaining intact, regardless of
various degrees of noise in the image.
To avoid the condition where noisy pixels are replaced by other noisy pixels to maintain the quality of images from its
degraded noise version such as blur which often takes place during transmission, acquisition, storage, etc.
METHODS, RESULTS AND CONCLUSION: The performance corroboration of the proposed efficient denoising
algorithmis accomplished employing nine standard grayscale images. The size of all standard images kept 256x256 pixels
in this research. The proposed image denoising system has experimented on those images affected with 10% to 90% salt &
pepper noise density. Additionally, the performance of the existing state-of-art denoising techniques like AMF, MF, WMF,
UMF, and DBMF are contrasted with the proposed hybrid approach. The results showed that de-noised images obtained
for 10% to 90% densities levels by proposed hybrid approach are quite better than the quality of denoised images achieved
from WMF, UTMF, AMF, and DBMF methods. The proposed algorithm effectively eradicates salt and pepper noise for
lower to higher image noise densities levels.
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Papers by faiz ullah
many algorithms and filters have been planned to improve the image information. There are various noise removal
procedures to identify and remove the corrupted pixels. But several image de-noising algorithms apply the filter to the
overall image to filter non-corrupted pixels also. To overcome these weaknesses, we proposed an efficient denoising
algorithm by cascading Adaptive Median Filter (AMF) with Modified Decision Based Median Filter (MDBMF).
OBJECTIVES: To acquire an efficient denoising algorithm for impulse noise reduction by combining AMF and MDBMF
methods which are effective, efficient for denoising various kinds of images.
To retain the edges, prevent signal deterioration, and ensure non-corrupted image pixels are remaining intact, regardless of
various degrees of noise in the image.
To avoid the condition where noisy pixels are replaced by other noisy pixels to maintain the quality of images from its
degraded noise version such as blur which often takes place during transmission, acquisition, storage, etc.
METHODS, RESULTS AND CONCLUSION: The performance corroboration of the proposed efficient denoising
algorithmis accomplished employing nine standard grayscale images. The size of all standard images kept 256x256 pixels
in this research. The proposed image denoising system has experimented on those images affected with 10% to 90% salt &
pepper noise density. Additionally, the performance of the existing state-of-art denoising techniques like AMF, MF, WMF,
UMF, and DBMF are contrasted with the proposed hybrid approach. The results showed that de-noised images obtained
for 10% to 90% densities levels by proposed hybrid approach are quite better than the quality of denoised images achieved
from WMF, UTMF, AMF, and DBMF methods. The proposed algorithm effectively eradicates salt and pepper noise for
lower to higher image noise densities levels.
many algorithms and filters have been planned to improve the image information. There are various noise removal
procedures to identify and remove the corrupted pixels. But several image de-noising algorithms apply the filter to the
overall image to filter non-corrupted pixels also. To overcome these weaknesses, we proposed an efficient denoising
algorithm by cascading Adaptive Median Filter (AMF) with Modified Decision Based Median Filter (MDBMF).
OBJECTIVES: To acquire an efficient denoising algorithm for impulse noise reduction by combining AMF and MDBMF
methods which are effective, efficient for denoising various kinds of images.
To retain the edges, prevent signal deterioration, and ensure non-corrupted image pixels are remaining intact, regardless of
various degrees of noise in the image.
To avoid the condition where noisy pixels are replaced by other noisy pixels to maintain the quality of images from its
degraded noise version such as blur which often takes place during transmission, acquisition, storage, etc.
METHODS, RESULTS AND CONCLUSION: The performance corroboration of the proposed efficient denoising
algorithmis accomplished employing nine standard grayscale images. The size of all standard images kept 256x256 pixels
in this research. The proposed image denoising system has experimented on those images affected with 10% to 90% salt &
pepper noise density. Additionally, the performance of the existing state-of-art denoising techniques like AMF, MF, WMF,
UMF, and DBMF are contrasted with the proposed hybrid approach. The results showed that de-noised images obtained
for 10% to 90% densities levels by proposed hybrid approach are quite better than the quality of denoised images achieved
from WMF, UTMF, AMF, and DBMF methods. The proposed algorithm effectively eradicates salt and pepper noise for
lower to higher image noise densities levels.