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.

Lossless progressive compression of medical images

Abstract: This paper presents a lossless image compression method, which provides progressive transmission property andscalability. The proposed method enables the codec to have a asymmetric structure by employng a fast adaptivesubband decomposition and the optimization of the quantization parameter during arithmetic coding. This methodprovides a higher compression ratio than JPEG lossless mode. Keywords: lossless compression, progressive transmission, fast adaptive subband decomposition, conditioning con- text, optimization of quantization parameter 1. INTRODUCTION Image compression method can be classified into two different methods: lossy compression and lossless compression. In general, the lossless compression is required in applications such as medical imaging or satellite photography,where the reliability of reproduction of images is a critical factor. Two features which are most required to imagecompression, either lossy or lossless, would be (i) scalability and (ii) progressive transmission property, since (i)enables receivers with different resolutions to display a received picture without any postprocessing at the receiverand (ii) allows many multimedia services such as image browsing. Considering the utilization of still images, the

High Dynamic Range Imaging with JPEG XT

Abstract: JPEG XT (ISO/IEC 18477), the latest standardization initiative of the JPEG (ISO SC29WG01) committee, defines an image compression standard backward compatible with the well-known JPEG standard (ISO/IEC 10918-1). JPEG XT extends JPEG by features such as coding of images of higher bit depth, coding of floating point image formats representing high dynamic range images, lossless compression, and coding of alpha channels. All extensions are compatible with the legacy JPEG standard, and always allow the reconstruction of JPEG XT codestreams to images of eight bits per pixel. This chapter discusses the history and motivation for JPEG XT, provides insight into its design principles, and provides results on its performance.

Perceptually optimal compression for heterogeneous image content in the context of medical networked applications

Abstract: In medical networked applications, the server-generated application view, consisting of medical image content and synthetic text/GUI elements, must be compressed and transmitted to the client. To adapt to the local content characteristics, the application view is divided into rectangular patches, which are classified into content classes: medical image patches, synthetic image patches consisting of text on a uniform/natural/medical image background and synthetic image patches consisting of GUI elements on a uniform/natural/medical image background. Each patch is thereafter compressed using a technique yielding perceptually optimal performance for the identified content class. The goal of this paper is to identify this optimal technique, given a set of candidate schemes. For this purpose, a simulation framework is used which simulates different types of compression and measures the perceived differences between the compressed and original images, taking into account the display characteristics. In a first experiment, JPEG is used to code all patches and the optimal chroma subsampling and quantization parameters are derived for different content classes. The results show that 4:4:4 chroma subsampling is the best choice, regardless of the content type. Furthermore, frequency dependant quantization yields better compression performance than uniform quantization, except for content containing a significant number of very sharp edges. In a second experiment, each patch can be coded using JPEG, JPEG XR or JPEG 2000. On average, JPEG 2000 outperforms JPEG and JPEG XR for most medical images and for patches containing text. However, for histopathology or tissue patches and for patches containing GUI elements, classical JPEG compression outperforms the other two techniques.

Image and Video Coding

Abstract: The sections in this article are 1 Compression Framework For Still Images 2 Jpeg–Still-Image Compression Standard 3 Beyond JPEG: Wavelets 4 Beyond JPEG: Fractal Coding 5 Compression Framework For Video 6 Video Standards 7 MPEG-4 Standard 8 MPEG-7 and Multimedia Databases 9 Current and Future Research Issues 10 Acknowledgments