An efficient error resilience scheme based on wyner-ziv coding for region-of-Interest protection of wavelet based video transmission

In this paper, we propose a bandwidth efficient error resilience scheme for wavelet based video transmission over wireless channel by introducing an additional Wyner-Ziv (WZ) stream to protect region of interest (ROI) in a frame. In the proposed architecture, the main video stream is compressed by a generic wavelet domain coding structure and passed through the error prone channel without any protection. Meanwhile, the predefined ROI area related wavelet coefficients obtained after an integer wavelet transform will be specially protected by WZ codec in an additional channel during transmission. At the decoder side, the error-prone ROI related wavelet coefficients will be used as side information to help decoding the WZ stream. Different size of WZ bit streams can be applied in order to meet different bandwidth condition and different requirement of end users. The simulation results clearly revealed that the proposed scheme has distinct advantages in saving bandwidth comparing with fully applied FEC algorithm to whole video stream and in the meantime offer the robust transmission over error prone channel for certain video applications

A Detail Based Method for Linear Full Reference Image Quality Prediction

In this paper, a novel Full Reference method is proposed for image quality assessment, using the combination of two separate metrics to measure the perceptually distinct impact of detail losses and of spurious details. To this purpose, the gradient of the impaired image is locally decomposed as a predicted version of the original gradient, plus a gradient residual. It is assumed that the detail attenuation identifies the detail loss, whereas the gradient residuals describe the spurious details. It turns out that the perceptual impact of detail losses is roughly linear with the loss of the positional Fisher information, while the perceptual impact of the spurious details is roughly proportional to a logarithmic measure of the signal to residual ratio. The affine combination of these two metrics forms a new index strongly correlated with the empirical Differential Mean Opinion Score (DMOS) for a significant class of image impairments, as verified for three independent popular databases. The method allowed alignment and merging of DMOS data coming from these different databases to a common DMOS scale by affine transformations. Unexpectedly, the DMOS scale setting is possible by the analysis of a single image affected by additive noise.Comment: 15 pages, 9 figures. Copyright notice: The paper has been accepted for publication on the IEEE Trans. on Image Processing on 19/09/2017 and the copyright has been transferred to the IEE

Understanding How Image Quality Affects Deep Neural Networks

Image quality is an important practical challenge that is often overlooked in the design of machine vision systems. Commonly, machine vision systems are trained and tested on high quality image datasets, yet in practical applications the input images can not be assumed to be of high quality. Recently, deep neural networks have obtained state-of-the-art performance on many machine vision tasks. In this paper we provide an evaluation of 4 state-of-the-art deep neural network models for image classification under quality distortions. We consider five types of quality distortions: blur, noise, contrast, JPEG, and JPEG2000 compression. We show that the existing networks are susceptible to these quality distortions, particularly to blur and noise. These results enable future work in developing deep neural networks that are more invariant to quality distortions.Comment: Final version will appear in IEEE Xplore in the Proceedings of the Conference on the Quality of Multimedia Experience (QoMEX), June 6-8, 201

Dynamic Background Segmentation for Remote Reference Image Updating within Motion Detection JPEG2000

International audienceWe present in this paper a new system based on Motion JPEG2000 intended for road surveillance application. The system uses a reference image and consists in 4 processing steps, namely initialization phase where the first reference image is built, reference estimation, motion segmentation (foreground extraction, ROI mask), and JPEG2000 coding. A first order recursive filter is used to build a reference image that corresponds to the background image. The obtained background is sent to the decoder once for all. The reference image at the coder side is estimated according to a Gaussian mixture model. The remote reference image is updated when specific conditions are met. The updating remote reference is triggered according to the states of mobile objects in the scene (no, few or lot of mobiles). The motion detection given by classical background subtraction technique is performed in order to extract a binary mask. The motion mask gives the region of interest of the system. The JPEG2000 image coded with a ROI option is sent towards the decoder. The decoder receives, decodes the image and builds the implicit binary ROI mask. Then, the decoder builds the displayed image using the reference image, the current image and the mask

Robust Transmission of Images Based on JPEG2000 Using Edge Information

In multimedia communication and data storage, compression of data is essential to speed up the transmission rate, minimize the use of channel bandwidth, and minimize storage space. JPEG2000 is the new standard for image compression for transmission and storage. The drawback of Compression is that compressed data are more vulnerable to channel noise during transmission. Previous techniques for error concealment are classified into three groups depending on the Approach employed by the encoder and decoder: Forward Error Concealment, Error Concealment by Post Processing and Interactive Error Concealment. The objective of this thesis is to develop a Concealment methodology that has the capability of both error detection and concealment, be Compatible with the JPEG2000 standard, and guarantees minimum use of channel bandwidth. A new methodology is developed to detect corrupted regions/coefficients in the received Images the edge information. The methodology requires transmission of edge information of wavelet coefficients of the original image along with JPEG2000 compressed image. At the receiver, the edge information of received wavelet coefficients is computed and compared with the received edge information of the original image to determine the corrupted coefficients. Three methods of concealment, each including a filter, are investigated to handle the corrupted regions/coefficients. MATLAB™ functions are developed that simulate channel noise, image transmission Using JPEG2000 standard and the proposed methodology. The objective quality measure such as Peak-signal-to-noise ratio (PSNR), root-mean-square error (rms) and subjective quality Measure are used to evaluate processed images. The simulation results are presented to demonstrate The performance of the proposed methodology. The results are also compared with recent approaches Found in the literature. Based on performance of the proposed approach, it is claimed that the Proposed approach can be successfully used in wireless and Internet communications