Browsing by Author "Rane, Shantanu D."

Now showing 1 - 3 of 3
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    Structure and texture filling-in of missing image blocks in wireless transmission and compression applications
    (2001-04) Rane, Shantanu D.; Sapiro, Guillermo; Bertalmio, Marcelo
    An approach for filling-in blocks of missing data in wireless image transmission is presented in this paper. When compression algorithms such as JPEG are used as part of the wireless transmission process, images are first tiled into blocks of 8 × 8 pixels. When such images are transmitted over fading channels, the effects of noise can kill entire blocks of the image. Instead of using common retransmission query protocols, we aim to reconstruct the lost data using correlation between the lost block and its neighbors. If the lost block contained structure, it is reconstructed using an image inpainting algorithm, while texture synthesis is used for the textured blocks. The switch between the two schemes is done in a fully automatic fashion based on the surrounding available blocks. The performance of this method is tested for various images and combinations of lost blocks. The viability of this method for image compression, in association with lossy JPEG, is also discussed.
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    Wavelet-Domain Reconstruction of Lost Blocks in Wireless Image Transmission and Packet-Switched Networks
    (2001-07) Rane, Shantanu D.; Remus, Jeremiah; Sapiro, Guillermo
    A fast scheme for wavelet-domain interpolation of lost image blocks in wireless image transmission is presented in this paper. The algorithm is designed to be compatible with the wavelet-based JPEG2000 image compression standard. In the transmission of block-coded images, fading in wireless channels and congestion in packet-switched networks can cause entire blocks to be lost. Instead of using common retransmission query protocols, we reconstruct the lost block in the wavelet-domain using the correlation between the lost block and its neighbors. The algorithm first uses a simple method to determine the presence or absence of edges in the lost block. This is followed by an interpolation scheme, designed to minimize the blockiness effect, while preserving the edges or texture in the interior of the block. The interpolation scheme minimizes the square of the error between the border coefficients of the lost block and those of its neighbors, at each transform scale. The performance of the algorithm on standard test images, its low computational overhead at the decoder, and its performance vis-a-vis other reconstruction schemes, is discussed.