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Speaker: Dr. Ghada Al-Hudhud
 
Co-authors:
Prof. M. Ibrahim, De Montfort University, Leicester/UK
Prof. M. Alakaidi, De Montfort University, Leicester/UK
Abstract: Wavelet domain statistical models have been shown to be useful for certain applications, e.g. image compression, watermarking and Gaussian noise reduction. One of the main problems for wavelet-based compression is to overcome quantization error efficiently.  Inspired by Weber- Fechners Law, the work presented in this paper introduces a logarithmic model that approximates the non-linearity of human perception and partially pre-compensates for the effect of the display device. A logarithmic transfer function is proposed in order to spread the coefficients distribution in the wavelet domain in compliance with the human perceptual attributes. The standard deviation δ of the logarithmically scaled coefficients in a subband represents the average difference from the mean of the coefficients in that subband. The standard deviation is chosen as a measure of the visibility threshold within this subband. Computing the values of δs for all subbands results in a differential sensitivity quantization matrix for a chosen image. The quantization matrix is then scaled by a factor δ in order to provide the best trade-off between the visual quality and the bit-rate of the processed image. A major advantage of this model is to allow for observing the visibility threshold and automatically produce the quantization matrix that is content dependant and scalable without further interaction from the user.
 
Dr. Ghada Al-hudhud, Dr Ghada Alhudhud is currently working as assistant professor at the College of Computer and Information Sciences, King Saud University, Information Technology Department.  Dr. Ghada holds a PhD in Software Engineering and worked for years for teaching and as a researcher at De Montfort University, Leicester, UK. Dr. Ghada served as Head of Software Engineering Department at Al-Ahliya Amman University, Jordan. Main research interest covers the areas: Automating Image Compression techniques for still and video images, Biometric security systems, Intelligent multiagent based mobile robotic communication, Applying Swarm Intelligence techniques for multiple cooperative nano-robots.

   
Date: May 7, 2012

Time: 12:00-1:00pm

Location: Room 20, Building 20