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Adaptive Block Compressive Sensing: towards a real-time and low-complexity implementation

Published version
Peer-reviewed

Type

Article

Change log

Authors

Zammit, Joseph 
Wassell, Ian J 

Abstract

Adaptive block-based compressive sensing (ABCS) algorithms are studied in the context of the practical realization of compressive sensing on resource-constrained image and video sensing platforms that use single-pixel cameras, multi-pixel cameras or focal plane processing sensors. In this paper, we introduce two novel ABCS algorithms that are suitable for compressively sensing images or intra-coded video frames. Both use deterministic 2D-DCT dictionaries when sensing the images instead of random dictionaries. The first uses a low number of compressive measurements to compute the block boundary variation (BBV) around each image block, from which it estimates the number of 2D-DCT transform coefficients to measure from each block. The second uses a low number of DCT domain (DD) measurements to estimate the total number of transform coefficients to capture from each block. The two algorithms permit reconstruction in real time, averaging 8 ms and 26 ms for 256x256 and 12x512 greyscale images, respectively, using a simple inverse 2D-DCT operation without requiring GPU acceleration. Furthermore, we show that an iterative compressive sensing reconstruction algorithm (IDA), inspired by the denoising-based approximate message passing algorithm, can be used as a post-processing, quality enhancement technique. IDA trades off real-time operation to yield performance improvement over state-of-the-art GPU-assisted algorithms of 1.31 dB and 0.0152 in terms of PSNR and SSIM, respectively. It also exceeds the PSNR performance of a state-of-the-art deep neural network by 0.4 dB and SSIM by 0.0126.

Description

Keywords

Adaptive block compressive imaging, adaptive block compressive sensing, compressed sensing, deterministic sensing matrices, iterative reconstruction

Journal Title

IEEE Access

Conference Name

Journal ISSN

2169-3536
2169-3536

Volume Title

Publisher

IEEE
Sponsorship
Engineering and Physical Sciences Research Council (EP/L015889/1)