Finite precision wavelets for image coding: lossy and lossless compression performance evaluation

2002 ◽  
Author(s):  
M. Grangetto ◽  
E. Magli ◽  
G. Olmo
Keyword(s):  
Performance Evaluation ◽  
Image Coding ◽  
Lossless Compression ◽  
Finite Precision ◽  
Compression Performance

scholarly journals Efficient Lossless Compression of Multitemporal Hyperspectral Image Data

2018 ◽  
Vol 4 (12) ◽  
pp. 142 ◽  
Author(s):  
Hongda Shen ◽  
Zhuocheng Jiang ◽  
W. Pan
Keyword(s):  
Data Compression ◽  
Hyperspectral Image ◽  
Image Data ◽  
Lossless Compression ◽  
Large Data ◽  
Hyperspectral Data ◽  
Compression Performance ◽  
Temporal Correlations ◽  
Sensing Applications ◽  
Data Volume

Hyperspectral imaging (HSI) technology has been used for various remote sensing applications due to its excellent capability of monitoring regions-of-interest over a period of time. However, the large data volume of four-dimensional multitemporal hyperspectral imagery demands massive data compression techniques. While conventional 3D hyperspectral data compression methods exploit only spatial and spectral correlations, we propose a simple yet effective predictive lossless compression algorithm that can achieve significant gains on compression efficiency, by also taking into account temporal correlations inherent in the multitemporal data. We present an information theoretic analysis to estimate potential compression performance gain with varying configurations of context vectors. Extensive simulation results demonstrate the effectiveness of the proposed algorithm. We also provide in-depth discussions on how to construct the context vectors in the prediction model for both multitemporal HSI and conventional 3D HSI data.

scholarly journals ScaleQC: a scalable lossy to lossless solution for NGS data compression

2020 ◽  
Vol 36 (17) ◽  
pp. 4551-4559 ◽  
Author(s):  
Rongshan Yu ◽  
Wenxian Yang
Keyword(s):  
Lossless Compression ◽  
Supplementary Information ◽  
Next Generation Sequencing Data ◽  
Sequencing Data ◽  
Source Codes ◽  
Compression Performance ◽  
Data Rates ◽  
Quality Value ◽  
Ngs Data ◽  
Bit Stream

Abstract Motivation Per-base quality values in Next Generation Sequencing data take a significant portion of storage even after compression. Lossy compression technologies could further reduce the space used by quality values. However, in many applications, lossless compression is still desired. Hence, sequencing data in multiple file formats have to be prepared for different applications. Results We developed a scalable lossy to lossless compression solution for quality values named ScaleQC (Scalable Quality value Compression). ScaleQC is able to provide the so-called bit-stream level scalability that the losslessly compressed bit-stream by ScaleQC can be further truncated to lower data rates without incurring an expensive transcoding operation. Despite its scalability, ScaleQC still achieves comparable compression performance at both lossless and lossy data rates compared to the existing lossless or lossy compressors. Availability and implementation ScaleQC has been integrated with SAMtools as a special quality value encoding mode for CRAM. Its source codes can be obtained from our integrated SAMtools (https://github.com/xmuyulab/samtools) with dependency on integrated HTSlib (https://github.com/xmuyulab/htslib). Supplementary information Supplementary data are available at Bioinformatics online.

Investigation of Lossless Audio Compression using IEEE 1857.2 Advanced Audio Coding

2017 ◽  
Vol 6 (2) ◽  
pp. 422
Author(s):  
Teddy Surya Gunawan ◽  
Muhammad Khalif Mat Zain ◽  
Fathiah Abdul Muin ◽  
Mira Kartiwi
Keyword(s):  
Lossless Compression ◽  
Audio Coding ◽  
Audio Compression ◽  
Source File ◽  
Compression Performance ◽  
Audio Quality ◽  
Current State ◽  
Ieee Standard ◽  
Audio Files ◽  
Advanced Audio Coding

<p>Audio compression is a method of reducing the space demand and aid transmission of the source file which then can be categorized by lossy and lossless compression. Lossless audio compression was considered to be a luxury previously due to the limited storage space. However, as storage technology progresses, lossless audio files can be seen as the only plausible choice for those seeking the ultimate audio quality experience. There are a lot of commonly used lossless codecs are FLAC, Wavpack, ALAC, Monkey Audio, True Audio, etc. The IEEE Standard for Advanced Audio Coding (IEEE 1857.2) is a new standard approved by IEEE in 2013 that covers both lossy and lossless audio compression tools. A lot of research has been done on this standard, but this paper will focus more on whether the IEEE 1857.2 lossless audio codec to be a viable alternative to other existing codecs in its current state. Therefore, the objective of this paper is to investigate the codec’s operation as initial measurements performed by researchers show that the lossless compression performance of the IEEE compressor is better than any traditional encoders, while the encoding speed is slower which can be further optimized.</p>

A New Compression Method for Bayer Color Filter Array Images

2013 ◽  
Vol 321-324 ◽  
pp. 1219-1224
Author(s):  
Bao Tang Shan ◽  
Fa Nian Wang ◽  
Juan Gao
Keyword(s):  
Image Compression ◽  
High Performance ◽  
Lossless Compression ◽  
Color Filter ◽  
Test Results ◽  
Compression Method ◽  
Sampling System ◽  
Multiple Channel ◽  
Compression Performance ◽  
Filter Array

In order to improve the compression performance of Bayer CFA images exposed continuously, a new high performance remainder set near-lossless compression method is presented. Based on channel-separated-filtering, several typical Bayer CFA image compression methods are compared with the proposed remainder set algorithm. It is proved that the remainder set algorithm has not only the better compression performance, i.e., the lower bits per pixel (average about 2.16bpp), but also the better reconstructed CFA image PSNR (average about 52.31dB). Finally, the proposed method is employed in a multiple channel CMOS image sampling system and some test results are given.

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