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16 September 1996 Image quality prediction for bit-rate allocation
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Recent developments in image coding tend to promote schemes consisting of a great variety of coding algorithms applied to different parts of the image to code. This results in an improved rate-distortion behavior of the global system. The selection of the optimal coding method for a given region of an image is still a computationally intensive task, as most of the current schemes need to compute the result for all algorithms and to choose the most suited one. This paper investigates a method to predict the coding performance. This prediction is based on extracted features of the input image. The computation of those features, as well as the prediction itself, is computationally much less expensive than the exhaustive selection. The prediction system is based on neural networks. Selected image features and a set of representation of those features build the input of the network. The low computation cost also enables a dynamic distribution of the fixed bitrate over the different parts of the image, and therefore an algorithm capable to allocate bits to reach a constant quality over the whole image.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Pascal Fleury and Touradj Ebrahimi "Image quality prediction for bit-rate allocation", Proc. SPIE 2952, Digital Compression Technologies and Systems for Video Communications, (16 September 1996);


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