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Toward LargePixel Number HighSpeed Imaging Exploiting Time and Space Sparsity
Naoki NOGAMI Akira HIRABAYASHI Takashi IJIRI Jeremy WHITE
Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Vol.E100A
No.6
pp.12791285 Publication Date: 2017/06/01
Online ISSN: 17451337
DOI: 10.1587/transfun.E100.A.1279
Type of Manuscript: PAPER Category: Digital Signal Processing Keyword: highspeed camera, sparsity, compressed sensing, image completion, convex optimization,
Full Text: PDF>>
Summary:
In this paper, we propose an algorithm that enhances the number of pixels for highspeed imaging. Highspeed cameras have a principle problem that the number of pixels reduces when the number of frames per second (fps) increases. To enhance the number of pixels, we suppose an optical structure that blockrandomly selects some percent of pixels in an image. Then, we need to reconstruct the entire image. For this, a stateoftheart method takes threedimensional reconstruction strategy, which requires a heavy computational cost in terms of time. To reduce the cost, the proposed method reconstructs the entire image framebyframe using a new cost function exploiting two types of sparsity. One is within each frame and the other is induced from the similarity between adjacent frames. The latter further means not only in the image domain, but also in a sparsifying transformed domain. Since the cost function we define is convex, we can find the optimal solution using a convex optimization technique with small computational cost. We conducted simulations using grayscale image sequences. The results show that the proposed method produces a sequence, mostly the same quality as the stateoftheart method, with dramatically less computational time.

