Based On Wavelet And Compressed Sensing Technology Of Greenhouse Monitoring Research Of Image Compression

With the continuous development of agricultural science and technology, China’s demand for greenhouse growing need to capture the image of greenhouse environment monitoring site also will be increased, it is possible to generate vast amounts of data, resulting in large volumes of data transfer and storage costs. Therefore, it is necessary prior to transmission to the greenhouse environment monitoring system collected in the field of image compression processing. Taking Shenyang Agricultural University Kitayama base 10 # shed greenhouse environment monitoring live images of the original image, wavelet and compressive sensing theory greenhouse image compression processing, which will help solve the greenhouse environment monitoring system collected at the scene of the image data transmission difficult storage and pressure problems.Using wavelet technology, by Daubechies wavelet db10 two kinds of db4 and wavelets detailed comparative analysis of the best select the appropriate image compression Wavelet greenhouse environment monitoring system collected in the field. Optimal use of wavelets for image compression simulation, and detailed experimental procedures. Through the decomposition of the image reconstruction, direct observation of the greenhouse effect image compression, as well as data compression and error PSNR value analysis, it is clear that better compression effect reconstruction.The use of compressed sensing technology, the design of random measurement matrix analyzed by Gauss/Bernoulli random measurement matrix and Fourier measurement comparison matrix, obtained by Fourier measurement matrix is more suitable for the greenhouse environment monitoring system site capture and compression processing image data. While the reconstruction algorithm design were analyzed separately using orthogonal matching pursuit algorithm, based tracking method and nonlinear conjugate gradient method three algorithms greenhouse environment monitoring system collected in the field of image compression process, select the appropriate image of heavy greenhouse reconstruction algorithm. And using the algorithm of greenhouse environment monitoring system collected in the field of image compression processing numerical example, by direct observation of the reconstructed image compression greenhouse effect reconstructed image and peak signal to noise ratio and the error is worth the experiment feasible.