Discrete wavelet transform-based structural similarity for image quality assessment

Image quality assessment method plays a major role in image processing. Structural similarity (SSIM) is a novel image quality assessment method, and attracts a lot of attentions for its good performance and simple calculation. But it is proposed in pixel domain, a large computation load is introduced when using it to guide image processing algorithm in discrete wavelet transform (DWT) domain. And image processing in DWT domain has been very common. This paper proposes a discrete wavelet transform-based structural similarity (DWT-SSIM) method for image quality assessment. As it highlights human eyes’ sensitive frequency bands, the proposed measure has a better correlation with the judgment of human observers than SSIM. Furthermore, the method is easy to implement and embed in DWT domain processing algorithms.