Download Advances in Image and Graphics Technologies: Chinese by Tieniu Tan, Qiuqi Ruan, Shengjin Wang, Huimin Ma, Kaiqi PDF

By Tieniu Tan, Qiuqi Ruan, Shengjin Wang, Huimin Ma, Kaiqi Huang

This booklet constitutes the referred lawsuits of the eighth China convention on photograph and pix applied sciences and functions, IGTA 2014, held in Beijing, China, in June 2014. The 39 papers offered have been conscientiously reviewed and chosen from one hundred ten submissions. They hide quite a few points of study in photo processing and snap shots and comparable themes, together with item detection, trend acceptance, item monitoring, class, photograph segmentation, reconstruction, etc.

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Extra resources for Advances in Image and Graphics Technologies: Chinese Conference, IGTA 2014, Beijing, China, June 19-20, 2014. Proceedings

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3 (4) The threshold of texture complexity is computed as: TCth = 1 ( TCvertical − M TC + TChorizontal − M TC + TCangle − M TC ) . M TC (5) 50 W. Wang et al. A MB has high texture complexity while TCth>1, and I4MB is selected as the prediction block size; otherwise, I16MB is chosen. 2 Mode Decision for Chroma 8×8 Block Intra Prediction In the intra prediction mode decision algorithm, the conventional calculation times of Rate-Distortion-Optimization is 4×(9×16+4)=592, the prediction mode of chroma block is used as the large exterior loop.

From (a) to (d): noisy input, results of BLF, WLS filter and L0 smoothing filter A Retinex-Based Local Tone Mapping Algorithm Using L0 Smoothing Filter 3 43 Proposed Method The classic retinex algorithm has some drawbacks as described in section 2. These drawbacks are overcome if the proposed method is used. The input data for our algorithm are RGBE images. We need to convert from the RGBE image to the RGB image, and then convert from the RGB image to the HSV image. Luminance is obtained from the HSV image to perform the tone mapping process.

2 L0 Smoothing Filter L0 smoothing filter is an edge-preserving smoothing filter first proposed by Li Xu [4]. In order to sharpen the major edges of image while eliminate the low-amplitude structures, the filter calculates in an optimization framework using L0 gradient minimization. The optimization framework controls the number of edges through globally controlling the number of non-zero gradients. The optimization framework can be expressed as the following formula:   min   ( S p − I p ) 2 + λ C ( S )} S  p  C ( S ) = count {p (3) } ∂xSp + ∂ySp ≠ 0 (4) in which p is a pixel in the image; I is the original image; and S is the result image filtered by the L0 smoothing filter.

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