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.

Uniform quantization error for Laplacian sources with applications to JPEG standard

Abstract: In this paper we propose a novel method for computing JPEG quantization matrices based on desired mean square error, avoiding the classical trial and error procedure. First, we use a relationship between a Laplacian source and its quantization error when uniform quantization is used in order to find a model for uniform quantization error. Then we apply this model to the coefficients obtained in the JPEG standard once the image to be compressed has been transformed by the discrete cosine transform. This allows us to compress an image using JPEG standard under a global MSE constraints and a set of local constraints determined by JPEG standard and visual criteria. Simulations show that our method generates better quantization matrices than the classical method scaling the JPEG default quantization matrix, with a cost lower than the coding, decoding and error measuring procedure.

Lossless compression of one-bit audio

Abstract: The paper introduces the coding technique that is used by the Super Audio CD system for lossless compression of 64 times oversampled one-bit audio data. The technique has been coined "DST" (direct stream transfer). The individual steps in the encoding and decoding process are detailed. The performance of the lossless compression algorithm, as a function of various music genres, is discussed. It is shown that 74 minutes of both stereo and multi-channel music, which translates to 12.5 GB of raw data, fit on the 4.7 GB Super Audio disc after compression. An extension to the algorithm for future professional use of higher sampling rates is made. The lossless compression performance is demonstrated with wide-band 256 Fs recordings, and 128 and 64 Fs down converted versions of these, demonstrating the scalability of the algorithm.

On lossless and lossy compression of step size matrices in JPEG coding

Abstract: Many image or video coding standards that are based on discrete cosine transform (DCT) rely on a step size matrix to normalize the DCT coefficients prior to quantization. The JPEG lossy image coding standard, for example, transmits the step size matrix as part of the bit-stream. In this study we present several low complexity lossless and lossy compression schemes that are applicable to the step size matrix, these schemes do not introduce any distortion to the decoded image data, and can be used in transcoding or to provide additional compression in storage applications. Experimental results show that on average the step size matrix of a JPEG file can be stored using 29% of the original bit requirement.

Integrated Digital Architecture for JPEG Image Compression

Abstract: This paper presents the architecture and design of a JPEG compressor in hardware. The system is a functional unit of a compressor chip, divided in four major parts: color space converter and downsampler, 2-D DCT module, quantization and entropy coding. Architectures for these four parts were designed and described in VHDL. The results of the VHDL mapping into Altera Flex 10K FPGAs are also herein presented.

ZPEG: A hybrid DPCM-DCT based approach for compression of Z-stack images

Abstract: Modern imaging technology permits obtaining images at varying depths along the thickness, or the Z-axis of the sample being imaged. A stack of multiple such images is called a Z-stack image. The focus capability offered by Z-stack images is critical for many digital pathology applications. A single Z-stack image may result in several hundred gigabytes of data, and needs to be compressed for archival and distribution purposes. Currently, the existing methods for compression of Z-stack images such as JPEG and JPEG 2000 compress each focal plane independently, and do not take advantage of the Z-signal redundancy. It is possible to achieve additional compression efficiency over the existing methods, by exploiting the high Z-signal correlation during image compression. In this paper, we propose a novel algorithm for compression of Z-stack images, which we term as ZPEG. ZPEG extends the popular discrete-cosine transform (DCT) based image encoder to compress Z-stack images. This is achieved by decorrelating the neighboring layers of the Z-stack image using differential pulse-code modulation (DPCM). PSNR measurements, as well as subjective evaluations by experts indicate that ZPEG can encode Z-stack images at a higher quality as compared to JPEG, JPEG 2000 and JP3D at compression ratios below 50∶1.