Abstract: As Image quality analysis is one of the most important measures in image research. The Objective of quality analysis is to check the quality of an image or to generate a better transformation for future automated image development. The quality of image can be monitored in two ways that is subjective & objective. In the past years various subjective & objective techniques have emerged for image quality analysis but those are valid for single camera images. Very less work has been done in quality assessment of Multi-camera images. The quality of multicamera images can be influenced by various factors such as camera features, calibration of camera, and number of camera units used for capturing the event. Multicamera images have two types of distortions: - a) Photometric distortion & b) Geometric distortion. The relative distortion between two or individual camera images are the main factor while evaluating the required quality of final image. Both these distortion can be measured in terms of index as Luminance, contrast (LC index), spatial motion (SM) & edge-based structural. The entire indexes are then combined and processed to obtain the perceived quality of multicamera image. This work describes a review on different image quality analysis techniques with different quality parameters and various types of distortion in the image.
Keywords: PSNR, SSIM, MSE, MSSSIM, MIQM.