Smoothness-Constrained Image Recovery from Block-Based Random Projections
This addresses visual quality issues in image recovery for applications like compression or transmission, but it is incremental as it builds on existing block-based methods.
The paper tackles the problem of visual artifacts in images reconstructed from block-wise random projections by proposing a method that enforces smoothness across block borders using partially overlapping blocks and a fast preview. The result is a quality improvement that can be assessed visually and through metrics like PSNR and SSIM.
In this paper we address the problem of visual quality of images reconstructed from block-wise random projections. Independent reconstruction of the blocks can severely affect visual quality, by displaying artifacts along block borders. We propose a method to enforce smoothness across block borders by modifying the sensing and reconstruction process so as to employ partially overlapping blocks. The proposed algorithm accomplishes this by computing a fast preview from the blocks, whose purpose is twofold. On one hand, it allows to enforce a set of constraints to drive the reconstruction algorithm towards a smooth solution, imposing the similarity of block borders. On the other hand, the preview is used as a predictor of the entire block, allowing to recover the prediction error, only. The quality improvement over the result of independent reconstruction can be easily assessed both visually and in terms of PSNR and SSIM index.