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 compression of data, in particular grib1 files

Abstract: The method for compressing 3D data, in particular 3D meteorological data and, more specifically 3D data in GRIB1 format, wherein the 3D data comprises several layers of 2D data, comprises the steps of (a) determining the differences between respective adjacent data within each of the 2D data layer so as to obtain 2D differential data layers, (b) determining the differences between the differential data of respective adjacent 2D differential data layers, and (c) compressing the 2D differential data layers obtained in step (b) using a 2D data compression such as e.g. JPEG LS or JPEG 2000.

Color-component bit allocation scheme for JPEG 2000 parallel codec

Abstract: A new bit allocation scheme for JPEG 2000 systems in parallel-distributed environments is proposed. In recent years, super high-definition images are being used for not only digital cinema also alternative services e.g. real-time sports in theaters. In general, such high-definition images are divided into small segments, such as tiles or components, and compressed. However, this process leads to low coding efficiency. In contrast, our proposed scheme controls the bit allocation ratio for each color-component separately by using the quantizer properties available in the JPEG 2000 standard. Simulation results show that the proposed scheme achieves the same coding performance as the non parallel-distributed approach.

Study on the application of SPIHT algorithm based on the spectral transformation in color image lossless compression

Abstract: In this paper, a new method to reduce spectral redundancy with SHIRCT was represented. It was advanced that the compression ratio of SPIHT code with different SHIRCT transformation parameters tends to be equival when the parameter r\ tends to 0. The way of reducing spatial redundancy by using wavelet transformation and the algorithm of image lossless compression applying SPIHT is researched too. The experiment results show that the algorithm can greatly improve the lossless compression efficiency on color image. The average compression ratio with the algorithm was increased about 19.43% than the ZIP lossless compression algorithm.