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Abstract
JPEG is the most commonly utilized image coding standard for storage and transmission purposes. It achieves a good rate–distortion trade-off, and it has been adopted by many, if not all, handheld devices. However, often information loss occurs due to transmission error or damage to the storage device. To address this problem, various coefficient recovery methods have been proposed in the past, including a divide-and-conquer approach to speed up the recovery process. However, the segmentation technique considered in the existing method operates with the assumption of a bi-modal distribution for the pixel values, but most images do not satisfy this condition. Therefore, in this work, an adaptive method was employed to perform more accurate segmentation, so that the real potential of the previous coefficient recovery methods can be unleashed. In addition, an improved rewritable adaptive data embedding method is also proposed that exploits the recoverability of coefficients. Discrete cosine transformation (DCT) patches and blocks for data hiding are judiciously selected based on the predetermined precision to control the embedding capacity and image distortion. Our results suggest that the adaptive coefficient recovery method is able to improve on the conventional method up to 27% in terms of CPU time, and it also achieved better image quality with most considered images. Furthermore, the proposed rewritable data embedding method is able to embed 20,146 bits into an image of dimensions .
Highlights
Despite the emerging technologies, such as 3D video and augmented reality, the still image remains one of the most popular forms of media in use
We improve Ong et al.’s image coefficient recovery method [7], and propose a rewritable data hiding method which exploits the fact that the removed coefficients can be recovered with high accuracy
We put forward a rewritable data embedding method by exploiting the fact that coefficients could be removed from an image I and later recovered to form the image Ir, where I and Ir are visually similar
Summary
Despite the emerging technologies, such as 3D video and augmented reality, the still image remains one of the most popular forms of media in use. Li et al [6] improved Uehara et al.’s method by using linear optimization approach and further extended its application to recover both DC and AC coefficients. This method can recover the overall structure and intensities when DC and AC coefficients are missing, and the recovered output images attain high SSIM values. Tan et al.’s method is designed to embed data into an encrypted JPEG image, the quality of the decrypted-recovered image is low, because it removes all the relevant coefficient(s) in every region for data embedding without considering the distortion caused.
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