Texture description and segmentation through fractal geometry
Computer Vision, Graphics, and Image Processing
Issues in vision modeling for perceptual video quality assessment
Signal Processing
Fuzzy fractal dimensions and fuzzy modeling
Information Sciences: an International Journal
Algorithms to estimating fractal dimension of textured images
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
Performance of Video Telephony Services in UMTS using Live Measurements and Network Emulation
Wireless Personal Communications: An International Journal
Computers in Biology and Medicine
Complex wavelet structural similarity: a new image similarity index
IEEE Transactions on Image Processing
The lacunarity of colour fractal images
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Quantifying color image distortions based on adaptive spatio-chromatic signal decompositions
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Fractal dimension and lacunarity of psoriatic lesions: a colour approach
BEBI'09 Proceedings of the 2nd WSEAS international conference on Biomedical electronics and biomedical informatics
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
No-reference quality assessment using natural scene statistics: JPEG2000
IEEE Transactions on Image Processing
VSNR: A Wavelet-Based Visual Signal-to-Noise Ratio for Natural Images
IEEE Transactions on Image Processing
Fractal Dimension of Color Fractal Images
IEEE Transactions on Image Processing
A distortion measure for blocking artifacts in images based on human visual sensitivity
IEEE Transactions on Image Processing
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Vision is a complex process that integrates multiple aspects of an image: spatial frequencies, topology and colour. Unfortunately, so far, all these elements were independently took into consideration for the development of image and video quality metrics, therefore we propose an approach that blends together all of them. Our approach allows for the analysis of the complexity of colour images in the RGB colour space, based on the probabilistic algorithm for calculating the fractal dimension and lacunarity. Given that all the existing fractal approaches are defined only for gray-scale images, we extend them to the colour domain. We show how these two colour fractal features capture the multiple aspects that characterize the degradation of the video signal, based on the hypothesis that the quality degradation perceived by the user is directly proportional to the modification of the fractal complexity. We claim that the two colour fractal measures can objectively assess the quality of the video signal and they can be used as metrics for the user-perceived video quality degradation and we validated them through experimental results obtained for an MPEG-4 video streaming application; finally, the results are compared against the ones given by unanimously-accepted metrics and subjective tests.