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Compressive Imaging of Color Images
| Content Provider | CiteSeerX |
|---|---|
| Author | Nagesh, Pradeep Li, Baoxin |
| Abstract | In this paper, we propose a novel compressive imaging framework for color images. We first introduce an imaging architecture based on combining the existing single-pixel Compressive Sensing (CS) camera with a Bayer color filter, thereby enabling acquisition of compressive color measurements. Then we propose a novel CS reconstruction algorithm that employs joint sparsity models in simultaneously recovering the R, G, B channels from the compressive measurements. Experiments simulating the imaging and reconstruction procedures demonstrate the feasibility of the proposed idea and the superior quality in reconstruction. |
| File Format | |
| Journal | IEEE ICASSP |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Color Image Compressive Imaging Single-pixel Compressive Sensing Novel C Reconstruction Algorithm Compressive Color Measurement Reconstruction Procedure Imaging Architecture Novel Compressive Imaging Framework Bayer Color Filter Compressive Measurement Superior Quality Joint Sparsity Model |
| Content Type | Text |
| Resource Type | Article |
