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In this paper, we investigate the field of direct visual odometry and specifically the implementation of hybrid approaches between deep learning and classical hand-crafted methods. We introduce a new approach that integrates a deblurring module with a ...

Several color spaces defined in the literature are obtained from the RGB space through non-linear transforms, potentially limiting their applicability in a regularization context. Therefore, in this paper, we introduce three new color spaces, QTLC-...${}_{}^{\mathrm{}}$${}_{}^{\mathrm{}}$${}_{}{}_{}$${}_{}{}_{}$${}_{}^{\mathrm{}}$${}_{}^{\mathrm{}}$

Camera motion introduces spatially varying blur due to the depth changes in the 3D world. This work investigates scene configurations where such blur is produced under parallax camera motion. We present a simple, yet accurate, Image Compositing ...

Low-light imaging using a hand-held camera is a challenging task due to excessive noise in the scene. Most of the existing methods try to address this problem either by denoising an image captured using high ISO or by deblurring an image captured using ...

Edge is widely used in blind deconvolution methods to provide the information source for the deblurring process. In the natural images, the blurring can be shown in any directions on edges randomly. However, the previous edge-based deconvolution methods ...

Existing works address the problem of generating high frame-rate sharp videos by separately learning the frame deblurring and frame interpolation modules. Most of these approaches have a strong prior assumption that all the input frames are blurry ...

Infrared image has lower resolution, unclear gray level, more concentrated gray distribution and less obvious texture, which is far from meeting the needs of human eyes for resolution, this paper proposes a Super-resolution reconstruction algorithm of ...

Image super-resolution and deblurring are two highly ill-posed problems that are usually dealt separately. However, real-world images are often low-resolution and have complex blurring. This paper focuses on ordinary natural scene images and ...

We propose a new motion blur descriptor to model the general planar motion of a rigid object and develop a practical algorithm to deblur planar motion from dual images, while the planar motion may include both rotation and translation. We propose a ...

We present and analyze an approach to image reconstruction problems with imperfect forward models based on partially ordered spaces---Banach lattices. In this approach, errors in the data and in the forward models are described using order intervals. The ...

The use of special digital image processing for removal of the blur which results quite often from a mutual relative motion of the optical sensor and object during the exposure is considered. The problem of blur removal from a digital image belongs to ...

We present a fast restoration-recognition algorithm for scanning motion-blurred QR codes on handheld and wearable devices. We blindly estimate the blur from the salient edges of the code in an iterative optimization scheme, alternating between image ...

In this paper, we have developed Real-Time optical image stabilization system which uses high frame rate (HFR) video sequence captured by high speed camera head in order to stabilize jitter due to undesired camera motion while handling camera head by ...

Motion blur is usually generated when people captured a picture in the daily life. This kind of blur is often non-liner motion and may cause the blurred contents seriously in this image. Hence, how to remove the blurred image into a clear image becomes ...

In this paper we study the problem of blind deconvolution. Our analysis is based on the algorithm of Chan and Wong [2] which popularized the use of sparse gradient priors via total variation. We use this algorithm because many methods in the literature ...

Images taken in low-light conditions with handheld cameras are often blurry due to the required long exposure time. Although significant progress has been made recently on image deblurring, state-of-the-art approaches often fail on low-light images, as ...

We propose a simple yet effective 0-regularized prior based on intensity and gradient for text image deblurring. The proposed image prior is motivated by observing distinct properties of text images. Based on this prior, we develop an efficient ...

We consider a class of quasi-variational inequalities (QVIs) for adaptive image restoration, where the adaptivity is described via solution-dependent constraint sets. In previous work we studied both theoretical and numerical issues. While we were able ...

We present a framework to super-resolve planar regions found in urban scenes and other man-made environments by taking into account their 3D geometry. Such regions have highly structured straight edges, but this prior is challenging to exploit due to ...

This paper presents a new method for deblurring photos using a sharp reference example that contains some shared content with the blurry photo. Most previous deblurring methods that exploit information from other photos require an accurately registered ...