EURASIP Journal on Advances in Signal Processing
An Edge-Preserving Super-Precision for Simultaneous Enhancement of Spacial and Grayscale Resolutions
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
An adaptive projected subgradient approach to learning in diffusion networks
IEEE Transactions on Signal Processing
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In this paper, we present a novel iterative MPEG super-resolution method based on an embedded constraint version of Adaptive projected subgradient method [Yamada & Ogura 2003]. We propose an efficient operator that approximates convex projection onto a set characterizing framewise quantization, whereas a conventional method can only handle a convex projection defined for each DCT coefficient of a frame. By using the operator, the proposed method generates a sequence that efficiently approaches to a solution of super-resolution problem defined in terms of quantization error of MPEG compression.