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This work proposes techniques for demosaicing multi-spectral images obtained from a single sensor architecture. This is a new problem. Compressed Sensing (CS) based formulations can recover images by exploiting the sparsity of the images in the wavelet domain. In this work, we improve upon existing techniques by accounting for the hierarchical (tree-structured) correlation that exists among the wavelet...
Recently Compressive Sensing (CS) has shown great potential in the field of Image processing applications. In this paper we propose a novel CS based technique for simultaneous compression and despeckling of Synthetic Aperture Radar (SAR) images. We incorporate Dual Tree Complex Wavelet Transform (DT-CWT) based denoising within a sparse regularization frame work and solve by a fast projected Landweber...
In Wireless Body Area Networks (WBAN) the energy consumption is dominated by sensing, processing and communication. Previous Compressed Sensing (CS) based solutions to EEG tele-monitoring over WBAN's could only reduce the communication cost. In this work, we propose to reduce the sensing and processing energy costs as well, by randomly under-sampling the signal. We formulate a theoretically sound...
Low cost RGB-D sensors such as the Microsoft Kinect have enabled the use of depth data along with color images. In this work, we propose a multi-modal approach to address the problem of removal of fences/occlusions from images captured using a Kinect camera. We also perform depth completion by fusing data from multiple recorded depth maps affected by occlusions. The availability of aligned image and...
This paper addresses the issue of magnetic resonance (MR) Image reconstruction at compressive sampling (or compressed sensing) paradigm followed by its segmentation. To improve image reconstruction problem at low measurement space, weighted linear prediction and random noise injection at unobserved space are done first, followed by spatial domain de-noising through adaptive recursive filtering. Reconstructed...
In this digital era medical image security is important as they carry highly personal data, which should be kept away from the hackers and unauthorized persons, as these images are transmitted/stored among hospitals and also by health insurance companies. Chaos based cryptography/security has been increased in recent years. In this paper we proposed an algorithm, in which security can be given along...
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