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A method for image recovery in the DFT domain

Authors: Peining Tao; Ahmet M. Eskicioglu;

A method for image recovery in the DFT domain

Abstract

In image authentication research, a common approach is to divide a given image into a number of smaller blocks, and embed a fragile watermark into each and every block. The modifications can therefore be detected in the blocks that have been tampered with. The literature includes many authentication techniques for detecting modifications only. In this paper, we propose a method for recovering the damaged blocks using the magnitudes of DFT coefficients. If a given block is considered to be damaged, we divide it into 2x2 blocks, and replace the magnitude of the DFT coefficient F(0,0) with the corresponding magnitude of the original image. As the F(0,0) coefficients are always real, we quantized them and round them off. The file containing all of these coefficients are sent from the sender to the receiver using a public key scheme. As an image authentication system, we will use the scheme proposed by Wong and Memon. In their proposal, the image is partitioned into IxJ blocks, and a watermark is inserted into each block.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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