A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
The visible differences predictor: an algorithm for the assessment of image fidelity
Digital images and human vision
What's wrong with mean-squared error?
Digital images and human vision
Digital Image Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
A distortion measure for blocking artifacts in images based on human visual sensitivity
IEEE Transactions on Image Processing
Image quality assessment based on included angle cosine and discrete 2-D wavelet transform
CCDC'09 Proceedings of the 21st annual international conference on Chinese Control and Decision Conference
Content-partitioned structural similarity index for image quality assessment
Image Communication
| Hi-index | 0.00 |
We present a full reference objective image quality assessment technique which is based on the properties of the human visual system (HVS). It consists of two major components: 1) structural similarity measurement (SSIM) between the reference and distorted images, mimicking the overall functionality of HVS in a top down frame work. 2) A visual attention model which indicates perceptually important regions in the reference image based on the characteristics of intermediate and higher visual processes through the use of Importance Maps. Structural similarity in a region is weighted, depending on the perceptual importance of the region to arrive at Perceptual Structural Similarity Metric (PSSIM) indicative of the image quality.