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.

Image quality comparison between JPEG and JPEG2000. I. Psychophysical investigation

Abstract: The original JPEG compression standard is efficient at low to medium levels of compression with relatively low levels of loss in visual image quality and has found widespread use in the imaging industry. Excessive compression using JPEG however, results in well-known artifacts such as "blocking" and "ringing," and the variation in image quality as a result of differing scene content is well documented. JPEG 2000 has been developed to improve on JPEG in terms of functionality and image quality at lower bit rates. One of the more fundamental changes is the use of a discrete wavelet transform instead of a discrete cosine transform, which provides several advantages both in terms of the way in which the image is encoded and overall image quality. This study involves a comparison of subjective image quality between JPEG and JPEG 2000 to establish whether JPEG 2000 does indeed demonstrate significant improvements in visual quality. A particular focus of this work is the inherent scene dependency of the two algorithms and their influence on subjective image quality results. Further work on the characterization of scene content is carried out in a connected study [S. Triantaphillidou, E. Allen, and R. E. Jacobson, "Image quality comparison between JPEG and JPEG2000. II. Scene dependency, scene analysis, and classification"

Adaptive predictive multiplicative autoregressive model for medical image compression

Abstract: An adaptive predictive multiplicative autoregressive (APMAR) method is proposed for lossless medical image coding. The adaptive predictor is used for improving the prediction accuracy of encoded image blocks in our proposed method. Each block is first adaptively predicted by one of the seven predictors of the JPEG lossless mode and a local mean predictor. It is clear that the prediction accuracy of an adaptive predictor is better than that of a fixed predictor. Then the residual values are processed by the multiplicative autoregressive (MAR) model with Huffman coding. Comparisons with other methods [MAR, space-varying MAR (SMAR) and adaptive JPEG (AJPEG) models] on a series of test images show that our method is suitable for reversible medical image compression.

Improved detection and evaluation for JPEG steganalysis

Abstract: Detection of information-hiding in JPEG images is actively delivered in steganalysis community due to the fact that JPEG is a widely used compression standard and several steganographic systems have been designed for covert communication in JPEG images. In this paper, we propose a novel method of JPEG steganalysis. Based on an observation of bi-variate generalized Gaussian distribution in Discrete Cosine Transform (DCT) domain, neighboring joint density features on both intra-block and inter-block are extracted. Support Vector Machines (SVMs) are applied for detection. Experimental results indicate that this new method prominently improves a current art of steganalysis in detecting several steganographic systems in JPEG images. Our study also shows that it is more accurate to evaluate the detection performance in terms of both image complexity and information hiding ratio.

JPEG 2000 compression of unfocused light field images based on lenslet array slicing

Abstract: This paper proposes an algorithm for lossy compression of unfocused light field images. The raw light field is preprocessed by demosaicing, devignetting and slicing of the raw lenset array image. The slices are then rearranged in tiles and compressed by the standard JPEG 2000 encoder. The experimental analysis compares the performance of the proposed method against the direct compression with JPEG 2000, and JPEG XR, in terms of BD-PSNR gain and bit rate reduction. Obtained results show that the proposed method outperforms direct application of the reference state of the art image encoders.

On the impact of histogram sparseness on some lossless image compression techniques

Abstract: Most of the image compression techniques currently available were designed mainly with the aim of compressing continuous-tone natural images. However, if this assumption is not verified, such as in the case of histogram sparseness, a degradation in compression performance may occur. In this paper, we analyze the impact of histogram sparseness in three state-of-the-art lossless image compression techniques: JPEG-LS, CALIC and lossless JPEG-2000. Moreover, we propose a simple procedure for on-line histogram packing, which holds nearly the same improvement as offline histogram packing. Results of its effectiveness when associated with JPEG-LS are presented.