Department of Computer Science and Information Systems

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Author: search.filters.author.Rohil, Mukesh KumarSubject: search.filters.subject.Fuzzy logic

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    A novel Venus’ visible image processing neoteric workflow for improved planetary surface feature analysis
    (Springer, 2024-03) Rohil, Mukesh Kumar
    The article presents a novel methodology that comprises of end-to-end Venus’ visible image processing neoteric workflow. The visible raw image is denoised using Tri-State median filter with background dark subtraction, and then enhanced using Contrast Limited Adaptive Histogram Equalization. The multi-modal image registration technique is developed using Segmented Affine Scale Invariant Feature Transform and Motion Smoothness Constraint outlier removal for co-registration of Venus’ visible and radar image. A novel image fusion algorithm using guided filter is developed to merge multi-modal Visible-Radar Venus’ image pair for generating the fused image. The Venus’ visible image quality assessment is performed at each processing step, and results are quantified and visualized. In addition, fuzzy color-coded segmentation map is generated for crucial information retrieval about Venus’ surface feature characteristics. It is found that Venus’ fused image clearly demarked planetary morphological features and validated with publicly available Venus’ radar nomenclature map.
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    Exploring possible aplications of fuzzy logic in imulation of three-dimensional visualisation using Remote Sensing data
    (Geospatial World, 2009) Rohil, Mukesh Kumar
    The paper explores various possibilities of application of fuzzy logic in simulating visualization of three-dimensional view of some area using remote sensing data. Author intends to use fuzzy logic for implementation of this task because of limited utilization of traditional algorithmic approach or logic in dealing with uncertainty and incomplete data and knowledge. At first, the paper illustrates the terms Fuzzy logic, Simulation, Three-Dimension, Visualization, remote sensing and remote sensing data. Then it dictates the inability and shortcomings of the traditional algorithmic and data representation approaches in handling the complexity involved with three-dimensional visualization and representation of both remote sensing data and information derived by analysis of remote sensing data. On the framework specified above, the paper further illustrates that we can apply fuzzy logic in most of the techniques used for three-dimensional visualization, both at hardware and software level. At last, the paper also explores the possibility of applying fuzzy logic in estimation of depth from stereo, texture, shading and motion, all in the context of simulation of three-dimensional visualization of remote sensing data.