A progressive image transmission scheme which combines transform coding with the human visual system (HVS) model is developed. The adaptivetransform coding of W.H. Chen and C.H. Smith (1977) is utilized to classify a...
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A progressive image transmission scheme which combines transform coding with the human visual system (HVS) model is developed. The adaptivetransform coding of W.H. Chen and C.H. Smith (1977) is utilized to classify an image into four equally populated subblocks based on their AC energies. The modulation transfer function (MTF) of the HVS model is obtained experimentally, based on processing a number of test images. A simplified technique for incorporating the MTF into the discrete cosine transform (DCT) domain is utilized. In the hierarchical image buildup, the image is first reconstructed from the DC coefficients of all subblocks. Further transmission hierarchy of transform coefficients and consequent image buildup are dependent on their HVS weighted variances. The HVS weighted reconstructed images are compared to the ones without any weighting at several stages. The HVS weighted progressive image transmission results in perceptually higher quality images compared to the unweighted scheme.
A hi-fi audio codeC with an improved adaptivetransform coding (ATC) algorithm is developed using digital signal processors (DSP's). An audio signal with a 20 kHz bandwidth sampled at 48 kHz is coded at a rate of ...
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A hi-fi audio codeC with an improved adaptivetransform coding (ATC) algorithm is developed using digital signal processors (DSP's). An audio signal with a 20 kHz bandwidth sampled at 48 kHz is coded at a rate of 128 kb/s. The algorithm utilizes adaptive block size selection, which is effective for pre-echo suppression. A modified discrete cosine transform (MDCT) with a simple window set is employed to reduce block boundary noise without decreasing the performance of transform coding. In addition, a fast MDCT calculation algorithm, based on a fast Fourier transform, is adopted. Weighted bit allocation is employed to quantize the transformed coefficients. The codeC is realized by a multiprocessor system composed of newly developed DSP boards. Subjective tests with the codeC show that the coding quality is comparable to that of compact disc signals.
This paper proposes a new approach to combined spatial (Intra) prediction and adaptivetransform coding in block-based video and image compression. Context-adaptive spatial prediction from available, previously decode...
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ISBN:
(纸本)9781424442959;9781424442966
This paper proposes a new approach to combined spatial (Intra) prediction and adaptivetransform coding in block-based video and image compression. Context-adaptive spatial prediction from available, previously decoded boundaries of the block, is followed by optimal transform coding of the prediction residual. The derivation of both the prediction and the adaptivetransform for the prediction error, assumes a separable first-order Gauss-Markov model for the image signal. The resulting optimal transform is shown to be a close relative of the sine transform with phase and frequencies such that basis vectors tend to vanish at known boundaries and maximize energy at unknown boundaries. The overall scheme switches between the above sine-like transform and discrete cosine transform (per direction, horizontal or vertical) depending on the prediction and boundary information. It is implemented within the H.264/AVC intra mode, is shown in experiments to significantly outperform the standard intra mode, and achieve significant reduction of the blocking effect.
We establish a principled framework for adaptivetransform coding. transformcoders are often constructed by concatenating an ad hoc choice of transform with suboptimal bit allocation and quantizer design. Instead, we...
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ISBN:
(纸本)0262122413
We establish a principled framework for adaptivetransform coding. transformcoders are often constructed by concatenating an ad hoc choice of transform with suboptimal bit allocation and quantizer design. Instead, we start from a probabilistic latent variable model in the form of a mixture of constrained Gaussian mixtures. Prom this model we derive a transform coding algorithm, which is a constrained version of the generalized Lloyd algorithm for vector quantizer design. A byproduct of our derivation is the introduction of a new transform basis, which unlike other transforms (PCA, DCT, etc.) is explicitly optimized for coding. Image compression experiments show adaptive transform coders designed with our algorithm improve compressed image signal-to-noise ratio up to 3 dB compared to global transform coding and 0.5 to 2 dB compared to other adaptive transform coders.
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