HDR and HR image reconstruction method based on sample prediction

The invention discloses an HDR and HR image reconstruction method based on sample prediction. An algorithm is divided into an off-line training part and an on-line learning part. The off-line training part comprises a learning sample collecting and organizing part and a classification predictor training part. The sample collecting process is divided into three classes to be conducted respectively according to the difference of scene brightness, and a clustering method is used for organizing sample files; afterwards, a linear or nonlinear predictor learning method is used for training a classification predictor, and HDR-HR reconstruction is conducted on multiple input LR-LDR images with different exposure parameters by an on-line reconstruction part. First, scene background brightness classification is conducted through the average images of input images, afterwards, according to a brightness classification result, the classification predictor which is well trained by the off-line training part is used for conducting high dynamic range and high resolution detailed information prediction on the input images, and at last high frequency information is reconstructed. By means of the HDR and HR image reconstruction method, effective imaging can be carried out in high-contrast scenes, and the objective that high resolution images and high dynamic range images can be reconstructed at the same time is achieved.