| Title | A New Approach to the Block-based Compressive Sensing |
| Publication Type | Conference Paper |
| Year of Publication | 2017 |
| Authors | Tian, Sen, Ye, Songtao, Iqbal, Muhammad Faisal Buland, Zhang, Jin |
| Conference Name | Proceedings of the 2017 International Conference on Computer Graphics and Digital Image Processing |
| Publisher | ACM |
| Conference Location | New York, NY, USA |
| ISBN Number | 978-1-4503-5236-9 |
| Keywords | Block-based Compressive Sensing, composability, compressive sampling, Cyber-physical systems, privacy, pubcrawl, resilience, Resiliency, The Number of Blocks, The Rang of Error Probability |
| Abstract | The traditional block-based compressive sensing (BCS) approach considers the image to be segmented. However, there is not much literature available on how many numbers of blocks or segments per image would be the best choice for the compression and recovery methods. In this article, we propose a BCS method to find out the optimal way of image retrieval, and the number of the blocks to which into image should be divided. In the theoretical analysis, we analyzed the effect of noise under compression perspective and derived the range of error probability. Experimental results show that the number of blocks of an image has a strong correlation with the image recovery process. As the sampling rate M/N increases, we can find the appropriate number of image blocks by comparing each line. |
| URL | http://doi.acm.org/10.1145/3110224.3110239 |
| DOI | 10.1145/3110224.3110239 |
| Citation Key | tian_new_2017 |
A New Approach to the Block-based Compressive Sensing