By Tieniu Tan, Qiuqi Ruan, Shengjin Wang, Huimin Ma, Kaiqi Huang
This ebook constitutes the referred lawsuits of the eighth China convention on picture and images applied sciences and purposes, IGTA 2014, held in Beijing, China, in June 2014. The 39 papers awarded have been conscientiously reviewed and chosen from a hundred and ten submissions. They conceal numerous facets of study in snapshot processing and pics and similar subject matters, together with item detection, trend popularity, item monitoring, category, photo segmentation, reconstruction, etc.
Read or Download Advances in Image and Graphics Technologies: Chinese Conference, IGTA 2014, Beijing, China, June 19-20, 2014. Proceedings PDF
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Extra resources for Advances in Image and Graphics Technologies: Chinese Conference, IGTA 2014, Beijing, China, June 19-20, 2014. Proceedings
4. The simulation waveform of intra prediction mode decision The synthesis results of the architecture are shown in Table 5; and table 6 shows the comparisons with related work. A Fast Mode Decision Algorithm and Its Hardware Design 55 Table 5. freq. 888 M Table 6. 8 4699 In the proposed architecture, with pipelining and parallel architecture, we can obtain 16 prediction pixels concurrently. Moreover, the throughout achieved by the proposed architecture is higher than the published results in [5,6,7], which make it possible to satisfy the requirement for the real time encoding.
Liu, and K. Xue where R ( x, y ) is the dynamic-range-compressed image; I ( x, y ) is the original image, * denotes the convolution operation; and F ( x, y ) is the surround function. In classical retinex algorithm, the surround function is Gaussian function. A drawback of the algorithm is that it induces halo artifacts along high-contrast edges. Under the assumption that the illuminant is spatially smooth, halo artifacts are due to the proximity of two areas of very different intensity. 2 L0 Smoothing Filter L0 smoothing filter is an edge-preserving smoothing filter first proposed by Li Xu .
The essential idea of image pyramid is to decompose the source image into different spatial resolutions through some mathematical operations. The most commonly used two image pyramids representation are Gaussian pyramid and Laplacian pyramid, and Laplacian pyramid can be derived from the Gaussian pyramid, which is a multi-scale representation obtained through a recursive low-pass filtering and down-sampling operations. G0 of Gaussian pyramid is equal to the original image, and the next level G1 is obtained by recursively down-sampling G0 and so on.