Closed loop optimization of image coding using subjective error criteria
نویسندگان
چکیده
This paper proposes a closed-loop optimization framework to improve image coding efficiency by searching DCT coefficients at the equivalent subjective quality to original coding result. The proposed framework shares a basic idea currently adopted in speech coding that searches optimal codes in closed-loop operation, evaluating the coded signal with perceptually weighted mean square error. To evaluate the perceptual quality in image coding, we introduce Masked PSNR that accounts masking effects, by which we apply the stepwise removal of subjectively negligible DCT coefficients. The result justifies the effectiveness of the proposed framework.
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