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

Embedding Authentication and DistortionConcealment in Images – A Noisy Channel Perspective

In multimedia communication, compression of data is essential to improve transmission rate, and minimize storage space. At the same time, authentication of transmitted data is equally important to justify all these activities. The drawback of compression is that the compressed data are vulnerable to channel noise. In this paper, error concealment methodologies with ability of error detection and concealment are investigated for integration with image authentication in JPEG2000.The image authentication includes digital signature extraction and its diffusion as a watermark. To tackle noise, the error concealment technologies are modified to include edge information of the original image.This edge_image is transmitted along with JPEG2000 compressed image to determine corrupted coefficients and regions. The simulation results are conducted on test images for different values of bit error rate to judge confidence in noise reduction within the received images

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

On the Application of Dictionary Learning to Image Compression

Signal models are a cornerstone of contemporary signal and image-processing methodology. In this chapter, a particular signal modelling method, called synthesis sparse representation, is studied which has been proven to be effective for many signals, such as natural images, and successfully used in a wide range of applications. In this kind of signal modelling, the signal is represented with respect to dictionary. The dictionary choice plays an important role on the success of the entire model. One main discipline of dictionary designing is based on a machine learning methodology which provides a simple and expressive structure for designing adaptable and efficient dictionaries. This chapter focuses on direct application of the sparse representation, i.e. image compression. Two image codec based on adaptive sparse representation over a trained dictionary are introduced. Experimental results show that the presented methods outperform the existing image coding standards, such as JPEG and JPEG2000

Error resilient image transmission using T-codes and edge-embedding

Current image communication applications involve image transmission over noisy channels, where the image gets damaged. The loss of synchronization at the decoder due to these errors increases the damage in the reconstructed image. Our main goal in this research is to develop an algorithm that has the capability to detect errors, achieve synchronization and conceal errors.;In this thesis we studied the performance of T-codes in comparison with Huffman codes. We develop an algorithm for the selection of best T-code set. We have shown that T-codes exhibit better synchronization properties when compared to Huffman Codes. In this work we developed an algorithm that extracts edge patterns from each 8x8 block, classifies edge patterns into different classes. In this research we also propose a novel scrambling algorithm to hide edge pattern of a block into neighboring 8x8 blocks of the image. This scrambled hidden data is used in the detection of errors and concealment of errors. We also develop an algorithm to protect the hidden data from getting damaged in the course of transmission

Steganography based image compression

The intention of image compression is to discard worthless data from image so as to shrink the quantity of data bits favored for image depiction, to lessen the storage space, broadcast bandwidth and time. Likewise, data hiding convenes scenarios by implanting the unfamiliar data into a picture in invisibility manner. The review offers, a method of image compression approaches by using DWT transform employing steganography scheme together in combination of SPIHT to compress an image

JPEG2000 compatible neural network based cipher

In this paper, an efficient encryption technique is proposed, especially for JPEG2000 compatible images.The technique uses a multilayer neural network to generate a pseudo-random sequence for transforming wavelet subbands into cipher subbands.The neural network generator takes 64 bit key as a startup seed with additional 64 bit key for initial weights and biases.At each layer, output is calculated by several iterations to increase the complexity of the pseudorandom sequence generation.In order to examine effectiveness of this approach, various tests including correlation, histogram, key space etc. are conducted on test images, and the results demonstrate the robustness of the proposed approach

ROBUST DECODING OF A 3D-ESCOT BITSTREAM TRANSMITTED OVER A NOISY CHANNEL

International audienceIn this paper, we propose a joint source-channel (JSC) decoding scheme for 3D ESCOT-based video coders, such as Vidwav. The embedded bitstream generated by such coders is very sensitive to transmission errors unavoidable on wireless channels. The proposed JSC decoder employs the residual redundancy left in the bitstream by the source coder combined with bit reliability information provided by the channel or channel decoder to correct transmission errors. When considering an AWGN channel, the performance gains are in average 4 dB in terms of PSNR of the reconstructed frames, and 0.7 dB in terms of channel SNR. When considering individual frames, the obtained gain is up to 15 dB in PSNR