Conference Papers

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    A Framework for Quality Enhancement of Multispectral Remote Sensing Images
    (Institute of Electrical and Electronics Engineers Inc., 2018) Suresh, S.; Das, D.; Lal, S.
    Researches in satellite image enhancement have been particularly confined to two major areas-contrast enhancement and image de noising of remote sensing images. The processing of relatively dark or shadowed images necessitates the need for robust remote sensing enhancement techniques. In this paper, a robust framework for quality enhancement of multispectral remote sensing images is proposed. The quantitative results of proposed algorithm and other existing remote sensing enhancement algorithms are calculated in terms of DE, NIQMC, BIQME, PisDist and CM on different remote sensing and other image databases. Results reveal that visual enhancement of the proposed algorithm is better than other existing remote sensing enhancement algorithms. Finally, the simulation experimental results show that proposed algorithm is effective and efficient for remotes sensing as well as natural images. © 2017 IEEE.
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    Secure transmission of Hyperspectral Images
    (Institute of Electrical and Electronics Engineers Inc., 2020) Srujana, O.S.; Mhala, N.C.; Pais, A.R.
    Hyperspectral Images (HSIs) are images that are captured across the electromagnetic spectrum. Hyperspectral images are represented using a three-dimensional (x,y,λ) data cube where dimension x and y represent the spatial dimension of a scene, and λ represents the spectral dimension of a scene. These images contain abundant information that has to be transmitted securely among the users for further processing. Visual Secret Sharing (VSS) is a modern cryptographic method used to send the visual data securely among n users. VSS scheme generates multiple shares of the secret image, and to recover secret image, these all shares need to be stacked together.In this paper, we propose a scheme for the secure transmission of hyperspectral images using VSS. We also introduce a band selection technique as a pre-processing step to reduce the redundancy and size of the image cube. The proposed scheme uses the super-resolution concept to increase the contrast of the resultant image, obtained from the VSS. We have performed the visual quality assessment of the reconstructed image using quantitative measurement parameters and we have compared the results with the existing VSS based Randomised VSS (RVSS) scheme. The experimental results showed that our proposed scheme achieves better reconstruction quality than the RVSS scheme and reconstructs HSI with a similarity of almost 76-95%. © 2020 IEEE.