mlsanityData to 14 Oct 2026

Lightweight Image Codec via Multi-Grid Multi-Block-Size Vector Quantization (MGBVQ)

arXiv 2209.12139 ↗First posted 25 Sep 2022cs.CVcited by 0

Not on the map. Why?

Abstract (arXiv)

A multi-grid multi-block-size vector quantization (MGBVQ) method is proposed for image coding in this work. The fundamental idea of image coding is to remove correlations among pixels before quantization and entropy coding, e.g., the discrete cosine transform (DCT) and intra predictions, adopted by modern image coding standards. We present a new method to remove pixel correlations. First, by decomposing correlations into long- and short-range correlations, we represent long-range correlations in coarser grids due to their smoothness, thus leading to a multi-grid (MG) coding architecture. Second, we show that short-range correlations can be effectively coded by a suite of vector quantizers (VQs). Along this line, we argue the effectiveness of VQs of very large block sizes and present a convenient way to implement them. It is shown by experimental results that MGBVQ offers excellent rate-distortion (RD) performance, which is comparable with existing image coders, at much lower complexity. Besides, it provides a progressive coded bitstream.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 8 of its 33 references that are in the map. First posted on arXiv 25 Sep 2022.

Builds on

8 of 33 references.

References · 8

  1. 2017Billion-scale similarity search with GPUscited by 2,497
  2. 2019An Introduction to Variational Autoencoderscited by 1,000
  3. 2018Variational image compression with a scale hyperpriorcited by 935
  4. 2016End-to-end Optimized Image Compressioncited by 696
  5. 2015Density Modeling of Images using a Generalized Normalization Transformationcited by 127
  6. 2019Image and Video Compression with Neural Networks: A Reviewcited by 86
  7. 2020PixelHop++: A Small Successive-Subspace-Learning-Based (SSL-based) Model for Image Classificationcited by 37
  8. 2020Holopix50k: A Large-Scale In-the-wild Stereo Image Datasetcited by 36

Built on by

Not cited yet.

Similar, not cited

Close in wording, no citation either way

  1. 2023LVQAC: Lattice Vector Quantization Coupled with Spatially Adaptive Companding for Efficient Learned Image Compression
  2. 2024Quantization-aware Matrix Factorization for Low Bit Rate Image Compression
  3. 2023Towards Accurate Image Coding: Improved Autoregressive Image Generation with Dynamic Vector Quantization
  4. 2025Binary Quadratic Quantization: Beyond First-Order Quantization for Real-Valued Matrix Compression
  5. 2023NVTC: Nonlinear Vector Transform Coding
  6. 2026Clustered Codebook Quantization for 2D Gaussian-based Image Compression
  7. 2025Exploiting Latent Properties to Optimize Neural Codecs
  8. 2023Extreme Image Compression using Fine-tuned VQGANs