The Light-Weighted Coding Schemes for Images Sharing on Mobile Devices

Jau-Ji Shen, Chun-Hsiu Yeh, and Jinn-Ke Jan


Cloud computing, mobile computing, image compression, image restoration


At the present time, there are so many computation requests of the mobile computing on clouding environment. In this paper, we addressed on the size and computation reduction during image transferring to the mobile device. To deal with this problem, the image processing techniques such as Discrete Wavelet Transformation (DWT), block Average Pixels Value (APV), and block Representation Pixel (RP) have been used to compress images. The key concept of our proposed light-weighted image coding is a lossy image compression technique which’s compress codes is a downscaled original image. Moreover, when the cloud sends the compressed small sized image to the mobile device for browsing, the decompression process Inverse Discrete Wavelet Transform (IDWT) or Neighboring Pixels Average Value (NPAV) restoration scheme can be used to backfill the small sized image to reconstruct a lossy original image if necessary. The advantage of our decompression concept is no extra information to be needed but only the small image itself for undergoing computation on the mobile device. The experimental results showed that, the lossy image Lena restored from its small sized version has PSNR 25.9 by IDWT, and the time cost of image compression and restoration only 0.0312 seconds.

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