Download Advances in Image and Video Technology: 5th Pacific Rim by Deepak Ghimire, Joonwhoan Lee (auth.), Yo-Sung Ho (eds.) PDF

By Deepak Ghimire, Joonwhoan Lee (auth.), Yo-Sung Ho (eds.)

The two-volume complaints LNCS 7087 + LNCS 7088 represent the complaints of the fifth Pacific Rim Symposium on picture and Video expertise, PSIVT 2011, held in Gwangju, Korea, in November 2011. the whole of seventy one revised papers used to be conscientiously reviewed and chosen from 168 submissions. the themes lined are: image/video coding and transmission; image/video processing and research; imaging and images and visualization; image/video retrieval and scene realizing; biomedical photograph processing and research; biometrics and snapshot forensics; and laptop imaginative and prescient applications.

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Additional info for Advances in Image and Video Technology: 5th Pacific Rim Symposium, PSIVT 2011, Gwangju, South Korea, November 20-23, 2011, Proceedings, Part I

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I. E. Jang, and M. Kim (a) (b) (c) Fig. 10. 7 We observed the stereoscopic images with a 3D monitor adopting DQCQS (Double Stimulus Continuous Quality Scale) subjective test [7]. At the first stage, original views were displayed to five participants. Each participant watched the views for 10 seconds and their new views for the same period, and evaluated the effect of the 3D depth. Two test sets were carried out in order to examine the 3D perception improvement. Depth perception was then subjectively judged on a scale of 1 (no improvement), 2 (mild improvement), 3 (average improvement), 4 (good improvement) and 5 (excellent improvement) in terms of 3D perception.

Images synthesized with different regularization factors (λ in Eq. (11)) are shown in Fig. 5. The top row shows the results with adaptive regularization, and the bottom shows those without it, where w(p) was fixed to 2000 for all pixels. When λ became larger (meaning stronger regularization), the resulting images by SR-based synthesis converged to I(t)↑ in both cases. Meanwhile, when λ became smaller (meaning weaker regularization), the resulting images were sharper, but some regions, such as occlusion boundaries, became noisy due to mis-registrations.

Future work will be focused on its real-time implementation. Our current implementation with unoptimized MATLAB codes performs at an unsatisfactory speed. We plan to transplant it to C++ and CUDA codes to improve the processing rate. Acknowledgments. This research is supported by the Strategic Information and Communication R&D Promotion Programs (SCOPE) of the Ministry of Internal Affairs and Communications, Japan. 1 Appendix Derivation of Mapping Function Here we show how to derive the point correspondence between two cameras α and β with a known depth z.

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