An Improved Compressive Sensing Technology And Its WiDi Application

Compressed sensing (CS) is a new technique for sampling and compression. It breaksthrough the Nyquist sampling for acquisition and made quite a stir in academic and industrycircles. On this basis,Lu Gan proposed block compressed sensing, which divided the originalimage into small block,and each block is processed independently. Block CS is faster insampling and reconstruction and lower in memory using. In this paper, we mainly do someresearch in reconstruction. Under the frame of block CS, we modify sections of sparerepresentation and reconstruction and propose our improved BCS (Block Compressed Sensing)algorithm. Here is summary of the main contents of the thesis:(1) Block CS based on the wavelet transform is proposed. In order to get rid of blockingartifacts, we use wavelet transform instead of Discrete Cosine Transform (DCT), in which theimage is divided into small blocks in time domain, and then each block is processed by wavelettransform. The experimental results show that there are not any blocking artifacts in thereconstruction image, and visual qualities are better than block CS based on the DCT. With ourmethod, the step of processing blocking artifacts can be elided. So the negative effect which isbrought by processing block artifacts can be avoided, and the time is saved.(2) An improved BCS remodeling based on the weighting made to observations matrix. Thelow frequency part weights greater in the image reconstruction, so the low-frequency part of theimage data is with higher accuracy in reconstruction; and the weight of high-frequency issmaller in reconstruction, the error is relatively large, but the image quality due to the influenceto the low-frequency component-based, so the entire image has better quality. This method ofreconstruction is at the expense of high-frequency components to ensure the low frequencycomponent of the reconstruction accuracy. And the reconstruction method also takes the structural information of the image into account, for smooth edges and contain small precludeedges, we use different different reconstruction methods, maximizing the reconstuction speedwithout affecting the effect of reconstruction quality at the same time.(3) In this paper, we do a plenty of experiments to test and verify advancement of ouralgorithm. In the reconstruction of nature images, our algorithm shows enormous advancementsno matter in time and visual qualities. In the reconstruction of SAR images, on the premise ofsimilar reconstruction qualities, compared with other algorithm, our algorithm show a hugeadvancement in time, and with the increasing of images, this advancement will become moreand more clearly. Finally, applying this BCS method to WiDi transmission, and logging the time,then remodeling the image.