Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In the traditional reconstruction algorithm for compressed sensing,  use the measurement matrix and the corresponding observed image to recover the target image. In the application of remote sensing, there are many multi-source and multi-temporal reference images that have similar information to that of the target image. ,  propose an algorithm to reconstruct the target image with information from multi-source and multi-temporal reference images to improve the image reconstruction accuracy, in other words, to improve the degree of similarity beten the reconstructed image and the target image. The basic principle of our method is to construct a penalty term with the similarity of the target sparse coefficient and the reference sparse coefficient to constrain the reconstruction process. The experimental results demonstrate the effectiveness of our method.
['Cong Fan', 'Lizhe Wang', 'Peng Liu', 'Ke Lu', 'Dingsheng Liu']
I am writing a research paper on a idea Compressed sensing based remote sensing image reconstruction via employing similarities of reference images
[{"from": "human", "value": "I am writing a research paper on a idea Compressed sensing based remote sensing image reconstruction via employing similarities of reference images"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In the traditional reconstruction algorithm for compressed sensing,  use the measurement matrix and the corresponding observed image to recover the target image. In the application of remote sensing, there are many multi-source and multi-temporal reference images that have similar information to that of the target image. ,  propose an algorithm to reconstruct the target image with information from multi-source and multi-temporal reference images to improve the image reconstruction accuracy, in other words, to improve the degree of similarity beten the reconstructed image and the target image. The basic principle of our method is to construct a penalty term with the similarity of the target sparse coefficient and the reference sparse coefficient to constrain the reconstruction process. The experimental results demonstrate the effectiveness of our method."}]