Quadtree coding with adaptive scanning order for space-borne image compression

Matlab code for QCAO published in Signal Processing: Image Communication, 2017
130 Downloads
Updated 26 Mar 2017

View License

Space-borne equipments produce very big images while their capacities of storage, calculation and transmission are limited, so low-complexity image compression algorithms are necessary. In this paper, we develop an efficient image compression algorithm based on quadtree in wavelet domain for this mission. First, we propose an adaptive scanning order for quadtree, which traverses prior the neighbors of previous significant nodes from bottom to the top of quadtree, so that more significant coefficients are encoded at a specified bit rate. Second, we divide the entire wavelet image to several blocks and encode them individually. Because the distortion-rate usually decreases as the level of the quadtree increases with the adaptive scanning order, to control bit rate for each block, we set the points exactly after coding each level of the quadtree as the candidate truncation points. The proposed method can provide quality, position and resolution scalability, which is simple and fast without any entropy coding, so it is very suitable for space-borne equipments. Experimental results show that it attains better performance compared with some state-of-the-art algorithms.

Cite As

Ke-Kun Huang (2024). Quadtree coding with adaptive scanning order for space-borne image compression (https://www.mathworks.com/matlabcentral/fileexchange/62283-quadtree-coding-with-adaptive-scanning-order-for-space-borne-image-compression), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2012a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Categories
Find more on Denoising and Compression in Help Center and MATLAB Answers

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Version Published Release Notes
1.0.0.0