Method and Architecture for Image and Video Signal Measurement and Applications
Measuring color image quality is important for image processing and computer vision tasks, such as remote sensing, medical imaging, consumer application, computer and robotic vision, and handwriting recognition. The most widely recognized method of determining color image quality is the subjective evaluation Mean Opinion Score (MOS), but subjective evaluation is time-consuming and thus inappropriate for many applications. Some methods make an objective image quality measurement by comparing an image to a reference image, but such methods may be stymied when no reference image is available for comparison. No-reference objective image quality metrics generally fail to correlate with human visual perception, which depends on the illumination environment, the characteristics of the perceiving eye and brain, exposure parameters, and image acquisition and processing systems. Accordingly, there is a need to measure color image quality in an objective fashion that is robust to lighting and distortion conditions, is correlated with human perception, is independent of image distortion, and can be implemented in real-time.