Shuiming Ye

Content based error detection and concealment for image transmission over wireless channel

In this paper, we present a novel content-based image error detection and error concealment algorithm to improve the image quality degraded during its transmission over a wireless channel. The damaged image blocks are detected by exploring the contextual information in images, such as their consistency and edge continuity. The statistical characteristics of missing blocks are then estimated, based on the types of their surrounding blocks (e.g., smoothness, texture and edge). Finally, different error concealment strategies are applied to different types of blocks in order to achieve better visual quality. Instead of assuming random errors in packets, we simulate the errors of wireless channels based on the Rayleigh model. Simulation results demonstrate that our proposed method is effective in terms of visual quality assessment and efficient in terms of computation complexity.

A CRYPTO SIGNATURE SCHEME FOR IMAGE AUTHENTICATION OVER WIRELESS CHANNEL

With the ambient use of digital images and the increasing concern on their integrity and originality, consumers are facing an emergent need of authenticating degraded images despite lossy compression and packet loss. In this paper, we propose a scheme to meet this need by incorporating a watermarking solution into a traditional crypto signature scheme to make the digital signatures robust to image degradations. The proposed approach is compatible with traditional crypto signature schemes except that the original image needs to be watermarked in order to guarantee the robustness of its derived digital signature. We demonstrate the effectiveness of this proposed scheme through practical experimental results as well as illustrative analysis.

Edge directed filter based error concealment for wavelet-based images

Edges in a natural image have important effects on the subjective visual quality. During the transmissions of wavelet-compressed images such as JPEG2000, errors in high frequency subbands will result in the effects like ring or ripple artifacts around edges. In this paper, we propose an error concealment algorithm to remove these annoying artifacts. This algorithm requires an edge directed filter. Although some known filters can be employed, we tailor-make a new edge directed filter which fits well in our algorithm. The proposed scheme firstly enhances the received damaged image using the edge directed filter. Then the recovered wavelet coefficients are rectified using two constraint functions, which are based on the statistical characteristics in the wavelet domain and the observation that correctly received data must remain unchanged. Simulation results show that the image quality has been significantly improved in terms of both objective and subjective evaluation.

Error resilient content-based image authentication over wireless channel

The pervasive distribution of digital images triggers an emergent need for authenticating degraded images by lossy compression and transmission. This paper proposes a robust content-based image authentication scheme for image transmissions over wireless channels. A robust multiscale based feature is used to generate the digital signature. The feature vector is reduced, encoded, and encrypted as signature of the image. This signature is then embedded into the image using a blind quantization based watermarking algorithm. Typical distortion patterns of malicious image manipulations and image transmissions over lossy channels are used for image authenticity verification. This scheme is also able to detect tampering areas in the attacked image. Experiments demonstrate the effectiveness and validity of our scheme.

A crypto signature scheme for image authentication over wireless channel

With the ambient use of digital images and the increasing concern on their integrity and originality, consumers are facing an emergent need of authenticating degraded images despite lossy compression and packet loss. In this paper, we propose a scheme to meet this need by incorporating a watermarking solution into a traditional crypto signature scheme to make the digital signatures robust to image degradations. The proposed approach is compatible with traditional crypto signature schemes except that the original image needs to be watermarked in order to guarantee the robustness of its derived digital signature. We demonstrate the effectiveness of this proposed scheme through practical experimental results as well as illustrative analysis.

Statistics- and spatiality-based feature distance measure for error resilient image authentication

Content-based image authentication typically assesses authenticity based on a distance measure between the image to be tested and its original. Commonly employed distance measures such as the Minkowski measures (including Hamming and Euclidean distances) may not be adequate for content-based image authentication since they do not exploit statistical and spatial properties in features. This paper proposes a feature distance measure for content-based image authentication based on statistical and spatial properties of the feature differences. The proposed statistics- and spatiality-based measure (SSM) is motivated by an observation that most malicious manipulations are localized whereas acceptable manipulations result in global distortions. A statistical measure, kurtosis, is used to assess the shape of the feature difference distribution; a spatial measure, the maximum connected component size, is used to assess the degree of object concentration of the feature differences. The experimental results have confirmed that our proposed measure is better than previous measures in distinguishing malicious manipulations from acceptable ones.

Error concealment for JPEG2000 images based on orthogonal edge directed filters

We propose an error concealment algorithm for JPEG2000 image transmissions over unreliable channels. Firstly, the local principal edge information in the damaged area is detected in the spatial domain. Then the proposed orthogonal edge directed filters (OEDFs) are applied to remove the ring or ripple artifact errors due to the loss of some wavelet transform (WT) bitplane data. Two kinds of constraints in WT domain are used for rectifying the recovered WT coefficients obtained from OEDFs, namely the WT known-value constraint and the empirical statistical constraint of the WT coefficients. Finally, this filtering-and-rectifying procedure is iterated until convergent. Simulation results have shown that both objective and subjective image quality have been improved by our proposed algorithm.

Watermarking based Image Authentication using Feature Amplification

In a typical content and watermarking based image authentication approach, a feature is extracted from the given image, and then embedded back into the image using a watermarking method. Since the entropy of the feature might be higher than the capacity of the watermarking scheme, or the feature is represented in a continuous domain, it has to be further quantized before embedding. The lost of information during quantization potentially degrades the overall performance of the authentication scheme. This paper propose a simple but effective approach that avoids the feature quantization by additive feature: the feature is firstly added into the image before watermark embedding, and latterly subtracted from the watermarked image. In our experiments, the proposed approach obtains larger achievable robustness/sensitivity region and has a smaller fuzzy region of authenticity than the typical approach

A quantization-based image authentication system

In this paper, we introduce a robust and secure digital signature scheme for image content authentication, by integrating content feature extraction, watermarking, cryptographic hashing, and digital signature into a unified framework. Given an image, a cryptographic signature is robustly generated based on extracted invariant features and then embedded into the DCT coefficients as watermarks. Quantization is applied to both robust feature extraction and watermarking. Simulation results further demonstrate the practicability of our method in terms of system robustness and system security.

Error resilient image authentication using feature statistical and spatial properties

The pervasive distribution of digital images triggers an emergent need of authenticating degraded images by lossy compression and transmission. This paper proposes a robust content-based image authentication scheme for image transmissions over lossy channels. Content-based image authentication typically assesses authenticity based on a distance measure of feature differences between the testing image and its original. Commonly employed distance measures such as the Minkowski measures may not be adequate for content-based image authentication since they do not exploit statistical and spatial properties of the feature differences. This proposed error resilient scheme is based on a statistics- and spatiality-based measure (SSM) of feature differences. This measure is motivated by an observation that most malicious manipulations are localized whereas acceptable manipulations cause global distortions. Experimental results show that SSM is better than previous used measures in distinguishing malicious manipulations from acceptable ones, and the proposed SSM-based scheme is robust to transmission errors and other acceptable manipulations, and is sensitive malicious image modifications.