Considering the trend towards adopting high efficiency picture coding schemes into digital broadcasting services, we investigate objective picture quality scales for evaluating digitally encoded still and moving pictures. First, the study on the objective picture quality scale for high definition still pictures coded by the JPEG scheme is summarized. This scale is derived from consideration of the following distortion factors; 1) weighted noise by the spatial frequency characteristics and masking effects of human vision, 2) block distortion, and 3) mosquito noise. Next, an objective picture quality scale for motion pictures of standard television coded by the hybrid DCT scheme is studied. In addition to the above distortion factors, the temporal frequency characteristics of vision are also considered. Furthermore, considering that all of these distortions vary over time in motion pictures, methods for determining a single objective picture quality value for this time varying distortion are examined. As a result, generally applicable objective picture quality scale is obtained that correlates extremely well with subjective picture quality scale for both still and motion pictures, irrespective of the contents of the pictures. Having an objective scale facilitates automated picture quality evaluation and control.

This paper discusses a new image resolution conversion method which converts not only spatial resolution but also amplitude resolution. This method involves considering impulse responses of image devices and human visual characteristics, and can preserve high image quality. This paper considers a system that digitizes the multilevel input image with high spatial resolution and low amplitude resolution using an image scanner, and outputs the image with low spatial resolution and high amplitude resolution on a CRT display. The algorithm thus reduces the number of pixels while increasing the number of brightness levels. Since a CRT display is chosen as the output device, the distribution of each spot in the display, which is modeled as a Gaussian function, is taken as the impulse response. The output image is then expressed as the summation of various amplitudes of the impulse response. Furthermore, human visual perception, which bears a nonlinear relationship to the spatial frequency component, is simplified and modeled with a cascade combination of low-pass and high-pass filters. The output amplitude is determined so that the error between the output image and the input image, after passing through the visual perception filter, is minimized. According to the results of a simulation, it is shown that image quality can be largely preserved by the proposed method, while significant image information is lost by conventional methods.