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Recently developed Compressive Sensing image sensor architectures tend to provide compact on-chip implementations to perform alternative acquisitions. On the other hand, the time of reconstruction generally limits possible applications taking advantage of those specific sensing schemes. This work proposes an entire Compressive Sensing system composed of an encoder (a dedicated imager top-level architecture)...
Compressive sensing [1] [2] measurements generally do not provide as much understandable information as traditional compressed domains. On the other hand, with the rise of compressive sensing image sensors, it becomes necessary to define relevant sensing schemes. Applying the same linear projection to reduced signal supports optimizes the reconstruction time and makes the sensing strategy more suitable...
We propose a novel approach to reconstruct High Dynamic Range images from few compressive measurements. The reconstruction algorithm directly merges the information of multi-capture bayerized images. It simultaneously performs demosaicing and naive predefined tone-mapping. Two different color spaces are taken into account at the reconstruction stage to add multiple constraints on the signal. The proposed...
This paper presents the evolutions of CMOS image sensors. From the early works, highly image processing oriented, the main research effort has then emphasized on image acquisition. To overcome the rising limitations of standard approaches and to promote new functionalities, several research directions are underway with promising results.
An image compressing technique for High Dynamic Range (HDR) image sensors is introduced. Compression is performed in two steps: Pixel value coding optimization followed by DCT-based (Discrete Cosine Transform) compression. A floating point coding technique is first used with a common exponent shared between pixels of the same block, and then a DCT is applied to each group of pixels. This new concept,...
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