The success of minimally invasive interventions and the remarkable technological medical progress have made endoscopic image enhancement a very active research field. Due to intrinsic domain characteristics surgical exercise, stereo images may suffer from different degradations which affect its quality. Therefore, in order provide surgeons with better visual feedback improve outcomes possible subsequent processing steps, namely, 3-D organ reconstruction/registration, it would be interesting...

Laparoscopic videos can be affected by different distortions which may impact the performance of surgery and introduce surgical errors. In this work, we propose a framework for automatically detecting identifying such their severity using video quality assessment. There are three major contributions presented in work (i) proposal novel enhancement laparoscopic surgery; (ii) publicly available database assessment evaluated expert as well non-expert observers (iii) objective including...

Many research efforts have been devoted to the improvement of stereo image coding techniques for storage or transmission. In this paper, we are mainly interested in lossy-to-lossless schemes images allowing progressive reconstruction. The most commonly used approaches compression based on disparity compensation techniques. basic principle involved technique first consists estimating map. Then, one is considered as a reference and other predicted order generate residual image. propose novel...

Holographic data play a crucial role in recent three-dimensional imaging as well microscopic applications. As result, huge amounts of storage capacity will be involved for this kind data. Therefore, it becomes necessary to develop efficient hologram compression schemes and transmission purposes. In paper, we focus on the shifted distance information, obtained by phase-shifting algorithm, where two sets difference need encoded. More precisely, nonseparable vector lifting scheme is...

In laparoscopic surgery, image quality can be severely degraded by surgical smoke, which not only introduces errors for the processing algorithms (used in guided surgery), but also reduces visibility of observed organs and tissues. To overcome these drawbacks, this work aims to remove smoke images using an preprocessing method based on a variational approach.In paper, we present physical model where is separated into two parts: direct attenuation veil propose efficient variational-based...

Radar composite reflectivity is a crucial component of Earth observation data, playing significant role in applications such as weather forecasting and climate disaster tracking. Due to the deployment challenges limited coverage meteorological radars, it impossible collect corresponding radar areas like mountains oceans. In cases, using deep learning methods reconstruct from satellite which has higher coverage, becomes an effective solution. However, data complex exhibits strong long-range...

With the increasing interest in holography three-dimensional imaging applications, use of hologram compression techniques is mandatory for storage and transmission purposes. The state-of-the-art approach aims at encoding separately each interference pattern by resorting to common still-image techniques. Contrary such an independent scheme, a joint coding scheme investigated this paper. More precisely, instead all patterns, it proposed that only two sets data be compressed taking into account...

Laparoscopic images and videos are often affected by different types of distortion like noise, smoke, blur nonuniform illumination. Automatic detection these distortions, followed generally application appropriate image quality enhancement methods, is critical to avoid errors during surgery. In this context, a crucial step involves an objective assessment the quality, which two-fold problem requiring both classification type affecting estimation severity level that distortion. Unlike...

Many existing works related to lossy-to-lossless image compression are based on the lifting concept. However, it has been observed that separable scheme structure presents some limitations because of processing performed along lines and columns. In this paper, we propose use a 2D non decomposition enables progressive reconstruction exact decoding images. More precisely, focus optimization all involved operators. respect, design prediction filters by minimizing variance detail signals....

Lifting schemes (LS) were found to be efficient tools for image coding purposes. Since LS-based decompositions depend on the choice of prediction/update operators, many research efforts have been devoted design adaptive structures. The most commonly used approaches optimize prediction filters by minimizing variance detail coefficients. In this article, we investigate techniques optimizing sparsity criteria focusing use an ℓ1 criterion instead ℓ2 one. output a filter may as input other...

In image guided surgery, stereo laparoscopes have been introduced to provide a 3D view of the organs during laparoscopic intervention. This video could possibly be used for other purposes than simple viewing: such as depth estimation, rendering scene and organ modeling. paper aims at reconstructing liver surface based on vision technique. The estimated can later registration preoperative model constructed from MRI/CT scans. For this purpose, we resort variational disparity estimation...

Lifting-based wavelet transform has been extensively used for efficient compression of various types visual data. Generally, the performance such coding schemes strongly depends on lifting operators used, namely prediction and update filters. Unlike conventional based linear filters, we propose, in this paper, to learn these by exploiting neural networks. More precisely, a classical Fully Connected Neural Network (FCNN) architecture is firstly employed perform update. Then, propose improve...

In laparoscopic surgery, image quality can be severely degraded by surgical smoke, which not only introduces error for the processing (used in guided surgery), but also reduces visibility of surgeons. this paper, we propose to enhance images decomposing them into unwanted smoke part and enhanced using a variational approach. The proposed method relies on observation that has low contrast inter-channel differences. A cost function is defined based prior knowledge solved an augmented...

In this paper, we present efficient bit allocation methods for stereo image coding purpose.Since the common idea behind most of existing compression schemes consists encoding a reference and residual images as well disparity map, mainly focus on issue between images.Generally, problem is solved in an empirical manner by looking optimal rates leading to minimum distortion value.Thanks recent approximations entropy functions, propose accurate fast appropriate open-loop-and closed-loop-based...

Recently, the amount of GI tract datasets is introduced more and by gathering from contests challenges. The most common task needs to solve that classify images into various classes. However, contributions existing approaches exhibit lots limitations. In this paper, we aim develop a computer-aided diagnosis system pathological findings in endoscopy images, can some pathologies including polyps, esophagitis, ulcerative -- colitis. To evaluate proposed work, use public dataset which...

In this paper, we develop an efficient bit allocation strategy for subband-based image coding systems. More specifically, our objective is to design a new optimization algorithm based on rate-distortion optimality criterion. To end, consider the uniform scalar quantization of class mixed distributed sources following Bernoulli-generalized Gaussian distribution. This model appears be particularly well-adapted data, which have sparse representation in wavelet basis. propose approximations...