Adaptive and automatic acquirement of optimal quality images in lower level image mining

The images taken from low-light level condition can not be resolved by human vision. We called the method, that these images are transformed into the visible images by human vision, lower level image mining (LLIM). We proposed a method called as the gradually flattening gray spectrum to mine a gray distribution information, proposed a method called as Zadeh-X transformation to implement a gray transformation to acquire a new image, and proposed a method which can predict transformation parameter by means of the subjective assessment results of the optimal quality images to adaptively, automatically and fast acquire the optimal quality images.