# Spatially Directional Predictive Coding for Block-based Compressive Sensing of Natural Images

arXiv: https://arxiv.org/abs/1404.7211 · HTML: https://mlsanity.com/paper/1404.7211/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Apr 2014.

## Built on by (most cited first, 1 of 1)

- [Deep Network for Image Compressed Sensing Coding Using Local Structural Sampling](https://mlsanity.com/paper/2402.19111/) (2024)

## Abstract (arXiv)

A novel coding strategy for block-based compressive sens-ing named spatially directional predictive coding (SDPC) is proposed, which efficiently utilizes the intrinsic spatial cor-relation of natural images. At the encoder, for each block of compressive sensing (CS) measurements, the optimal pre-diction is selected from a set of prediction candidates that are generated by four designed directional predictive modes. Then, the resulting residual is processed by scalar quantiza-tion (SQ). At the decoder, the same prediction is added onto the de-quantized residuals to produce the quantized CS measurements, which is exploited for CS reconstruction. Experimental results substantiate significant improvements achieved by SDPC-plus-SQ in rate distortion performance as compared with SQ alone and DPCM-plus-SQ.