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.

Post-processing for JPEG 2000 image coding using recursive line filtering based on a fuzzy control model

Abstract: In this paper, we propose a new method for removing coding artifacts appeared in JPEG 2000 coded images. The proposed method uses a fuzzy control model to control the weighting function for different image edges according to the gradient of pixels and membership functions. Regularized post-processing approach and recursive line algorithm are described in this paper. Experimental results demonstrate that the proposed algorithm can significantly improve image quality in terms of objective and subjective evaluation.

Resampling Tamper Detection Based on JPEG Double Compression

Abstract: JPEG compression and resampling operations appear frequently when image is tampered, hence the traces of JPEG compression and resampling are used to detect images. As JPEG compression and resampling operations affect the linear correlation between coefficients, so the traces of JPEG compression and the linear correlation are introduced when images are resampled and saved in JPEG format. Hence, the moment of DCT coefficient histogram are taken as the factor of JPEG compression, and due to the singular value decomposition can measure linear correlation between pixels well so that the mean value and variance of the singular values are extracted. At last, two types of features are extracted and trained by SVM. Experimental results show that proposed method has a good detection rate for resampling compression images, especially for rotation operation and the scale factor which greater than 1.

Novel approach to multispectral image compression on the Internet

Abstract: Still image coding techniques such as JPEG have been always applied onto intra-plane images. Coding fidelity is always utilized in measuring the performance of intra-plane coding methods. In many imaging applications, it is more and more necessary to deal with multi-spectral images, such as the color images. In this paper, a novel approach to multi-spectral image compression is proposed by using transformations among planes for further compression of spectral planes. Moreover, a mechanism of introducing human visual system to the transformation is provided for exploiting the psycho visual redundancy. The new technique for multi-spectral image compression, which is designed to be compatible with the JPEG standard, is demonstrated on extracting correlation among planes based on human visual system. A high measure of compactness in the data representation and compression can be seen with the power of the scheme taken into account.© (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Squashed JPEG Image Compression via Sparse Matrix

Abstract: To store and transmit digital images in least memory space and bandwidth image compression is needed. Image compression refers to the process of minimizing the image size by removing redundant data bits in a manner that quality of an image should not be degrade. Hence image compression reduces quantity of the image size without reducing its quality. In this paper it is being attempted to enhance the basic JPEG compression by reducing image size. The proposed technique is about amendment of the conventional run length coding for JPEG (Joint Photographic Experts Group) image compression by using the concept of sparse matrix. In this algorithm, the redundant data has been completely eliminated and hence leaving the quality of an image unaltered. The JPEG standard document specifies three steps: Discrete cosine transform, Quantization followed by Entropy coding. The proposed work aims at the enhancement of the third step which is Entropy coding.

Image Compression and File Formats

Abstract: As long as memory storage is at a premium, compression of documents and images was a necessity. While today storage is relatively inexpensive, the role of compression still plays an important part of digital imaging. While digital cameras have significant internal memory and the various memory cards can store in as much as 64 gigabytes of data, data compression is still required for the transmission of images and graphics across networks and even from the personal computer to a printer. Transmission of “movies” would be impossible without sophisticated compression algorithms. This chapter focuses on the compression methods developed for the digital still camera, but they have found considerable use in other fields of imaging where massive data sets need to be stored and retrieved for many imaging uses including medicine, graphic arts, HD TV, video conferencing, and digital entertainment. Here, JPEG, JPEG 2000, and some of the encoding techniques are demonstrated along with their advantages and disadvantages. Keywords: compression; JPEG; JPEG 2000; discrete cosine transforms; wavelets; Huffman coding; arithmetic coding; file formats; EXIF; DPCM