Complex Wavelet Structural Similarity: A New Image Similarity Index
University of California System · University of California, San Francisco · +2 more institutions
Abstract
We introduce a new measure of image similarity called the complex wavelet structural similarity (CW-SSIM) index and show its applicability as a general purpose image similarity index. The key idea behind CW-SSIM is that certain image distortions lead to consistent phase changes in the local wavelet coefficients, and that a consistent phase shift of the coefficients does not change the structural content of the image. By conducting four case studies, we have demonstrated the superiority of the CW-SSIM index against other indices (e.g., Dice, Hausdorff distance) commonly used for assessing the similarity of a given pair of images. In addition, we show that the CW-SSIM index has a number of advantages. It is…
Citation impact
- FWCI
- 32.61
- Percentile
- 100%
- References
- 71
Authors
5Topics & keywords
- Similarity (geometry)
- Artificial intelligence
- Structural similarity
- Wavelet
- Preprocessor
- Pattern recognition (psychology)
- Hausdorff distance
- Mathematics