Deep Learning-Based Event Data Coding: A Joint Spatiotemporal and Polarity Solution
Neuromorphic vision sensors, commonly referred to as event cameras, generate a massive number of pixel-level events, composed by spatiotemporal and polarity information, thus demanding highly efficient coding solutions.
Abdelrahman Seleem +3 more
doaj +1 more source
Lossless Compression Framework Using Lossy Prior for High-Resolution Remote Sensing Images
Lossless compression of remote sensing images is critically important for minimizing storage requirements while preserving the complete integrity of the data.
Enjia Gu +3 more
doaj +1 more source
High efficient shape coding based on the representation of contour and chain code
A high efficient lossless shape coding scheme was proposed based on the representation of contour and chain code. The object contours are firstly extracted and thinned to be single-pixel width.
Zhong-jie ZHU, Yu-e WANG, Gang-yi JIANG
doaj +2 more sources
Regression Wavelet Analysis for Lossless Coding of Remote-Sensing Data
N. Amrani +4 more
semanticscholar +1 more source
Regression Wavelet Analysis for Progressive-Lossy-to-Lossless Coding of Remote-Sensing Data
N. Amrani +3 more
semanticscholar +1 more source
Non-Uniform Entropy-Constrained <i>L</i><sub>∞</sub> Quantization for Sparse and Irregular Sources. [PDF]
Alecu AA +3 more
europepmc +1 more source
Refinements and Generalizations of the Shannon Lower Bound via Extensions of the Kraft Inequality. [PDF]
Merhav N.
europepmc +1 more source
Empirical Lossless Compression Bound of a Data Sequence. [PDF]
Li LM.
europepmc +1 more source
Learning to compress electrocardiogram signals on a quick response code. [PDF]
Srivastava A, Dewan D, Patra A, Sheet D.
europepmc +1 more source

