||Remote sensing images in the shooting process, affected by weather, cameralensquality , pixel displacement caused by flying, ambient environmental factors make it difficult to maintain the complete observation messages of image , causing the images have deviation or distortion, resulting in reduced image quality.|
Super-resolution reconstruction technology can break the image acquisition devices restrictionsand environmental restrictions , the basic concept of Super- resolution reconstruction technology is using the multiple images which have blur and noise ,making use of the characteristics of the image and combined with priori- information for data fusion to get the high-resolution images.
Super-resolution image reconstruction algorithm is divided into "single-image super-resolution reconstruction" and "multiple images super-resolution reconstruction": single image super-resolution reconstruction is use of low-resolution images toreconstruct a high-resolution images ; while multiple images super-resolution reconstruction is use of multiple low-resolution images which in the same scene, and the images have geometric deformation , making use of the characteristics of the image and combined with priori- information for data fusion to get the high-resolution images.
This study uses projection onto convex sets method (POCS) ,iterative back projection(IBP) and bicubic interpolation to process the image for four different conditions, in addition to use the Super-resolution image reconstruction algorithm to enhannce the quality of image , but also hope that through the different results to compare the difference between single-image processing and multiple-images processing.
In the End , use the Standard Deviation to detect the geometric accuracy of image ,to explore the relationship between definition and the geometric accuracy.