Lossless JPEG

About: Lossless JPEG is a research topic. Over the lifetime, 2415 publications have been published within this topic receiving 51110 citations. The topic is also known as: Lossless JPEG & .jls.

A New JPEG Resistant Color Image Watermarking Algorithm Based on Quantization Index Modulation

Abstract: A new color image watermarking algorithm with resistance to JPEG lossy compression based on Quantization Index Modulation (QIM) is proposed in this paper. As it is known, QIM method can achieve a good balance between the embedding bit rate, robustness and distortion between the original image and the composited image by modulating the source signal into different clusters. The corresponding DCT coefficients margins of any two color channels selected from the three as the source signal is substantiated could achieve a high level embedding robustness and a low level distortion in this paper. However, JPEG lossy compression could bring a destructive influence to the watermark since it discards pretty much image information. In this paper, a compensation function is designed to correct the errors caused by JPEG compression. Experiments show the algorithm proposed has a good performance to resist the high compression ratio JPEG lossy compression and other attacks.

Shape VQ-based adaptive predictive lossless image coder

Abstract: A new shape adaptive predictive lossless image coder is proposed. Three classes of block shapes are delineated with associated "optimum" predictors. Each image is partitioned into sub-blocks that are classified into one of the three classes using vector quantisation. The encoder then employs the predictor corresponding to the class of the block under consideration. Performance evaluation of the proposed coder in comparison with four other lossless coders including lossless JPEG indicates its superiority.

Analysis of Adaptive Binary Optimization for Lossless Medical Image Compression

Abstract: In modern sciences and technologies, images are the important source of scientific visualization. Image compression is concerned with minimizing the number of bits required to represent an image. Medical imaging techniques such as CT, MRI and PET modalities produce huge amounts of data. As a result, storage and transmission of image data electrically are prohibitive without the use of compression. This paper deals with analyzing the various functionality and features of adaptive binary optimization (ABO) technique based on Repetition and correlation coding for compressing a medical images using GUI in matlab.ABO is a process and a system for compressing image data having high correlation value. This technique is simple in implementation and utilizes less memory as compared to other lossless compression technique. Compressing the image without loss in the quality of the image make it an efficient lossless technique for medical image compression. Keywords—Repetition Coded Compression; high correlation; bitplane; lossless image data.

Hyperspectral image lossless compression based on integer wavelet transform and 3-D adaptive prediction

Abstract: Making use of the spectral correlation within the sub-image of hyperspectral images,a new lossless compression of hyperspectral images based on integer wavelet transform and 3D-adaptive prediction is studied in the paper.First,use 5/3 integer wavelet to analyze every band of hyper -spectral images,to the same sub -band of different bands,a new linear predictor is proposed.Neighboring pels are chosen to adaptively estimate predict -coefficient which remove most spatial and spectral redundancy,and then JPEG-LS is used to remove spectral redundancy.Experiments show that the algorithm can compress the data efficiently and work better than other compression algorithm and the algorithm is easy,so it can be easily achieved by hardware.