Muhammad Mohsin Riaz

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An image fusion technique for magnetic resonance imaging (MRI) and positron emission tomography (PET) using local features and fuzzy logic is presented. The aim of proposed technique is to maximally combine useful information present in MRI and PET images. Image local features are extracted and combined with fuzzy logic to compute weights for each pixel.(More)
—A technique for magnetic resonance brain image classification using perceptual texture features, fuzzy weighting and support vector machine is proposed. In contrast to existing literature which generally classifies the magnetic resonance brain images into normal and abnormal classes, classification with in the abnormal brain which is relatively hard and(More)
Improved guided image fusion for magnetic resonance and computed tomography imaging is proposed. Existing guided filtering scheme uses Gaussian filter and two-level weight maps due to which the scheme has limited performance for images having noise. Different modifications in filter (based on linear minimum mean square error estimator) and weight maps (with(More)
Singular value decomposition based through wall image enhancement is proposed which is capable of discriminating target, noise and clutter signals. The overlapping boundaries of clutter, noise and target signals are separated using fuzzy logic. Fuzzy inference engine is used to assign weights to different spectral components. K-means clustering is used for(More)
A three step based contrast enhancement technique is proposed for flood monitoring. The proposed technique takes pre and post images and apply different processing steps for generating flood map quickly without user interaction which is used by disaster management and rehabilitation authorities. A specific pre processing phase “contrast(More)
An entropy dependent compressive sensing based image fusion is proposed which adaptively adjusts the number of compressive measurements depending on the amount of information (computed using entropy). Since the computational complexity is dependent on the number of compressive measurements, the proposed scheme is more efficient and accurate. Simulation(More)
—A through wall image enhancement scheme based on Takagi-Sugeno fuzzy system and principal component analysis is proposed. The scheme incorporates spectral properties of image and textural properties of eigen components of image to assign weights. The scheme overcomes the empirical setting of inference engine and output membership functions. Simulation(More)