This paper presents an efficient fractal coding scheme for color images and demonstrates its experimental results. The proposed fractal coding scheme utilizes the correlation between a luminance component (Y) and two color difference components (Cr and Cb) of an input color image. The Y, Cr and Cb components are first decomposed to low and high frequency sub-band images. Fractal block coding is performed only on the lowest frequency sub-band images of Y, Cr
and Cb. The other high frequency sub-band images are encoded by vector quantization (VQ). In the fractal coding process for Y, each range block is encoded by a set of contractive affine transformations of its correspondent domain block. For Cr and Cb, on the other hand, only the range block average values are coded. The other fractal coded data of the correspondent range block of Y are applied also to Cr and Cb. The computer simulation experimental results show
that the coded and decoded color images obtained by the proposed scheme give higher SNR values and better image qualities compared to the conventional fractal coding scheme and JPEG.
This paper presnts a fast local motion estimation algorithm based on so called elementary motion detectors or EMDs. EMDs, modeling insect’s visual signal processing systems, have low computational complexity aspects and can thus be key components to realize such a fast local motion estimation algorithm. The contribution of the presented work is to introduce dual parameter estimators or DPEs by configuring EMDs so that they can estimate local motions in terms of both direction and speed mode parameters simultaneously. The estimated
local motion vectors are displayed as arrows superimposed over video image frames. The developed algorithm is implmented in a DirectShow application by using Mircosoft’s DirectX runtime library and is evaluated using various types of video image sequences. It is found to be able to estimate local motion vectors in real time even
in moderate PC computing platforms and hece no high profile hardware devices are needed for its real time operation.
This paper presents an improved fractal block coding scheme for still images. The proposed scheme employs a new technique which we call `sub-block luminance level shifting.' In fractal block coding, an input image is first partitioned into range blocks. Each range block is encoded by a set of contractive affine transformations of its corresponding domain block. One of the coded data for each range block is an average pixel value of the range block, which is used for luminance level shifting between the range block and the contracted domain block. In our proposed method, a range block is further partitioned into sub-blocks in some cases and an average value of each sub-block instead of the range block is used for luminance level shifting. We have proposed an improved fractal block coding scheme applying this sub-block luminance level shifting adaptively block-by-block basis and also combining this method with adaptive range block size fractal coding. The computer simulation results show that the proposed fractal coding scheme gives higher SNR (Signal-to- Noise Ratio) values and better image qualities compared to the conventional fractal block coding scheme.
KEYWORDS: Scalable video coding, Signal to noise ratio, Computer simulations, Quantization, Computer programming, Video, Video coding, Linear filtering, Microchannel plates, Information technology
This paper describes scalable coding schemes which use subband picture decomposition and motion compensated interframe prediction. In the scalable coding, a lower resolution picture can be obtained by decoding only a subset of the total bitstream, while a full resolution picture is obtained by decoding the total bitstream. Two types of scalable coding schemes are studied. In the first type (schemes A), an input picture is first decomposed to subband pictures, then MC prediction coding is carried out in the subband picture domain. In the second type (scheme B), MC prediction is first carried out in the full band picture domain and then subband decomposition is performed for the prediction difference picture. Coding performance for these two types of schemes was estimated by computer simulation experiments. The performance comparison between scalable and non scalable coding schemes was also carried out. The experimental results have demonstrated that the scheme B is superior to schemes A.
Once video coding standards are finalized, decoders are completely specified so that encoders from different providers can maintain the inter-operability. However, some of the encoding parameters such as the decision thresholds of the embedded quantizers and the buffer-control schemes still remain at designer's freedom. Taking advantage of this freedom, this paper concentrates on the design of encoders for existing decoders. More specifically, an entropy- constrained design approach is described only for the quantizer decision thresholds within encoders while the reconstruction levels and the variable-length code (VLC) table remain unchanged. The efficiency of the new method is demonstrated through an example of the well- known Lloyd-Max quantizers operating on broad-tailed generalized Gaussian distributed memoryless sources.
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