Picture coding: A review

By A. Netravali, J. Limb. 1980

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Citations in the corpus

End-to-end Optimized Image Compression (2016, methodology): “…existing image compression methods operate by linearly transforming the data vector into a suitable continuous-valued representation, quantizing its elements independently, and then encoding the resulting discrete representation using a lossless entropy code (Wintz, 1972; Netravali and Limb, 1980).”
High Speed Lossless Image Compression (2015, unknown): “The prediction residuals from delta coding tend to follow a two sided geometric distribution [19,16], where small differences are very common.”
Computational microstructure characterization and reconstruction: Review of the state-of-the-art techniques (2018, methodology): “The Gaussian pyramid [244] (aka, hierarchical discrete correlation [143]) is commonly used in image analysis to decorrelate the neighboring pixels (voxel in 3D) and arrive at a compact representation of the image (see [289] for a review on image compression techniques).”
The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS (2000, background): “Although there is room for creative combinations, the widely accepted observation [21] that prediction residuals in continuous-tone images are well modeled by a two-sided geometric distribution (TSGD) makes this model very appealing in image coding.”
Neural Network Approaches to Image Compression (1995, background): “As a result, a number of approaches to the problem are well established [6], [7], [8], [9], [10], [11], [12], [13], [14].”