Hitoshi Kiya

Lossless Data Hiding in the Spatial Domain for High Quality Images

A lossless data embedding method that inserts data in images in the spatial domain is proposed in this paper. Though a lossless data embedding method once distorts an original image to embed data into the image, the method restores the original image as well as extracts hidden data from the image in which the data are embedded. To guarantee the losslessness of data embedding, all pixel values after embedding must be in the dynamic range of pixels. Because the proposed method modifies some pixels to embed data and leaves other pixels as their original values in the spatial domain, it can easily keep all pixel values after embedding in the dynamic range of pixels. Thus, both the capacity and the image quality of generated images are simultaneously improved. Moreover, the proposed method uses only one parameter based on the statistics of pixel blocks to embed and extract data. By using this parameter, this method does not require any reference images to extract embedded data nor any memorization of the positions of pixels in which data are hidden to extract embedded data. In addition, the proposed method can control the capacity for hidden data and the quality of images conveying hidden data by controlling the only one parameter. Simulation results show the effectiveness of the proposed method; in particular, it offers images with superior image quality to conventional methods.

A Location-Map Free Reversible Data Hiding Method using Block-Based Single Parameter

This paper proposes a reversible data hiding method that embeds an L-level data sequence to images in the spatial domain. Though reversible data hiding once distorts the image to hide data into it, the distorted image is completely separated to the original image and the hidden data. The proposed method uses only one parameter to embed and extract data, and it extracts data without any location map. In addition, it can control embedding capacity according to payload for suppression of embedding distortion. Simulation results show the effectiveness of the proposed method.

Modulo arithmetic-based image watermarking and its theoretical analysis of image-quality

This paper proposes a watermarking method that hides an integer in an image by modifying the sum of the quantized discrete cosine transformed coefficients. Because modulo arithmetic-based modulation is applied to an integer to be embedded, less image distortion is achieved. Moreover, coefficients not being chosen to embed an integer are restored to their pre-quantized form, even though they are once quantized. The image-quality of a watermarked image is theoretically analyzed and is found to be superior to those of image-quality guaranteed watermarking methods.

An Efficient Reversible Image Authentication Method

This paper proposes an image authentication method that detects tamper and localizes tampered areas efficiently. The efficiency of the proposed method is summarized as the following three points. 1) This method offers coarse-to-fine tamper localization by hierarchical data hiding so that further tamper detection is suppressed for blocks labeled as genuine in the uppper layer. 2) Since the image feature description in the top layer is hidden over an image, the proposed method enciphers the data in the top layer rather than enciphers all data in all layers. 3) The proposed method is based on the reversible data hiding scheme that does not use highly-costed compression technique. These three points makes the proposed method superior to the conventional methods using compression techniques and methods using multi-tiered data hiding that requires integrity verification in many blocks even the image is genuine. Simulation results show the effectiveness of the proposed method.

Lossless Data Hiding in the Spatial Domain for Image Tamper Detection

This paper proposes lossless data hiding method for image tamper detection. The proposed method embeds data in images and extracts data from images in the spatial domain. This method restores the original image as well as extracts hidden data from an image conveying hidden data. The proposed method uses one and only one parameter for each image to control embed and extract data. An image is divided into several blocks, and the image feature description for the block is hidden into the corresponding block itself. Hidden descriptions extracted from an image and generated from the recovered image are compared to detect tampering. The image quality of an image with hidden data is high so that nobody is aware that data are hidden. Experimental results show the effectiveness of the proposed method

Lossless Data Embedding in the Spatial Domain

A lossless data embedding method that inserts data in images in the spatial domain is proposed in this paper. The proposed method restores the original image as well as extracts hidden data from an image in which data are embedded. One and only one parameter based on statistics of pixels is used to embed and extract data. This method requires neither any reference images nor memorization of positions of pixels in which data are hidden to extract embedded data. In addition, the proposed method can control the payload of hidden data and the quality of an image conveying hidden data by controlling the parameter. Simulation results show the effectiveness of the proposed method