Perceptual Hashing With Complementary Color Wavelet Transform and Compressed Sensing for Reduced-Reference Image Quality Assessment

Reduced Reference Quality Assessment Based on Watermarking and Perceptual Hashing

Geert Braeckman, Adriaan Barri, Gabor Fodor, Ann Dooms, Joeri Barbarien, Peter Schelkens , András Bohó, Li Weng #2,3 #1 Vrije Universiteit Brussel (VUB), Dept. of Electronics and Informatics (ETRO), Pleinlaan 2, B-1050 Brussels, Belgium. #2 Interdisciplinary Institute for Broadband Technology (IBBT), Dept. of Future Media and Imaging (FMI), Gaston Crommenlaan 8 (box 102), B-9050 Ghent, Belgium....

Reduced-Reference Image Quality Assessment based on saliency region extraction

In this paper, a novel saliency theory based RR-IQA metric is introduced. As the human visual system is sensitive to the salient region, evaluating the image quality based on the salient region could increase the accuracy of the algorithm. In order to extract the salient regions, we use blob decomposition (BD) tool as a texture component descriptor. A new method for blob decomposition is propos...

Compressed Image Hashing using Minimum Magnitude CSLBP

Image hashing allows compression, enhancement or other signal processing operations on digital images which are usually acceptable manipulations. Whereas, cryptographic hash functions are very sensitive to even single bit changes in image. Image hashing is a sum of important quality features in quantized form. In this paper, we proposed a novel image hashing algorithm for authentication which i...

Perceptual Image Hashing via Wave Atom Transform

Image authentication using LBP-based perceptual image hashing

Feature extraction is a main step in all perceptual image hashing schemes in which robust features will led to better results in perceptual robustness. Simplicity, discriminative power, computational efficiency and robustness to illumination changes are counted as distinguished properties of Local Binary Pattern features. In this paper, we investigate the use of local binary patterns for percep...