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/Keywords (Lossy Image Compression, Seam Identification, SPIHT Coding\r\n)
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/Subject (The project proposes the seam based on economical compression. In mobile transmission communications, image retargeting is usually required at the user end. However, content-based image retargeting is with high machine quality and is not acceptable for mobile devices with restricted computing power. The work throughout this paper addresses the increasing demand of signal delivery to terminals with discretionary resolutions, whereas not serious machine burden to the receiving finish. Throughout this paper, the principle of seam carving is incorporated into a wave codec \(i.e., SPIHT\). For each input image, block-based seam energy map is generated inside the picture element domain and so the entire variety wave process \(IWT\) is performed for the retargeted image. These area unit encoded keep with the resultant seam energy map. Experimental results shows that, the retargeted images shows better PSNR and MSE values as well as good compression ratios without loss of data.\r\n)
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K. Mallikarjuna, S. Ifthukar
Lossy Image Compression
Seam Identification
SPIHT Coding
The project proposes the seam based on economical compression. In mobile transmission communications, image retargeting is usually required at the user end. However, content-based image retargeting is with high machine quality and is not acceptable for mobile devices with restricted computing power. The work throughout this paper addresses the increasing demand of signal delivery to terminals with discretionary resolutions, whereas not serious machine burden to the receiving finish. Throughout this paper, the principle of seam carving is incorporated into a wave codec (i.e., SPIHT). For each input image, block-based seam energy map is generated inside the picture element domain and so the entire variety wave process (IWT) is performed for the retargeted image. These area unit encoded keep with the resultant seam energy map. Experimental results shows that, the retargeted images shows better PSNR and MSE values as well as good compression ratios without loss of data.
Efficient Lossy Image Compression Technique Based On Seam Identification and SPIHT Coding
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