No-reference image quality assessment for removal of processed and unprocessed noise

We present a fast no-reference quality measurement method based on the entropy analysis of the image structure. The information that an images carries is represented not only by intensity values but also their position in the image. We examine the behavior of the entropy by altering the positions to distinguish the image structure, noise and blur. We propose a method to rearrange the pixel placements using a random pixel scattering transform. Using this transform we firstly determine the local power of image structure relative to noise and then we obtain the quality index by combining this information with our proposed blur factor. We show that this method is useful to select denoising parameters automatically in both unprocessed (white Gaussian) and processed (frequency-dependent) noise when the reference image is not available. Our method is easy to implement and yet rivals state-of-the-art quality measurement approaches.