Michiharu Niimi

High-performance JPEG steganography using quantization index modulation in DCT domain

This paper presents two JPEG steganographic methods using quantization index modulation (QIM) in the discrete cosine transform (DCT) domain. The two methods approximately preserve the histogram of quantized DCT coefficients, aiming at secure JPEG steganography against histogram-based attacks. In comparison with F5 as a representative JPEG steganography, the proposed methods show high performance with regard to embedding rate, PSNR of stego image, and particularly histogram preservation.

A gray image compression using a Hilbert scan

Hilbert curve is one of the space-filling curves published by Peano. There are several applications using this curve such as image processing, computer hologram, etc. In this paper, we concentrate on a lossy compression technique for a gray image using the Hilbert curve. The merit of this curve is to pass through all points in a quadrant, and it always moves to the neighbor quadrant. Our method is based on this neighborhood property, by a simple segmentation of the scanned one-dimensional data using a zero order interpolation. From our experiments, we have confirmed that in spite of the simple computation in comparison to JPEG, acceptable quality images can be obtained at bit-rates above 0.6 bit/pixel.

Application of BPCS steganography to wavelet compressed video

This paper presents a steganography method using lossy compressed video which provides a natural way to send a large amount of secret data. The proposed method is based on wavelet compression for video data and bit-plane complexity segmentation (BPCS) steganography. In wavelet-based video compression methods such as 3-D set partitioning in hierarchical trees (SPIHT) algorithm and motion-JPEG2000, wavelet coefficients in discrete wavelet transformed video are quantized into a bit-plane structure and therefore BPCS steganography can be applied in the wavelet domain. 3-D SPIHT-BPCS steganography and motion-JPEG2000-BPCS steganography are presented and tested, which are the integration of 3-D SPIHT video coding and BPCS steganography and that of motion-JPEG2000 and BPCS, respectively. Experimental results show that 3-D SPIHT-BPCS is superior to motion-JPEG2000-BPCS with regard to embedding performance.

Application of QIM with dead zone for histogram preserving JPEG steganography

This paper presents two histogram preserving JPEG steganographic methods aiming at secure JPEG steganography against histogram-based attacks. The first one is a histogram quasi-preserving method, which uses quantization index modulation (QIM) at quantization step of DCT coefficients. Since a straightforward application of QIM causes a significant histogram change, a device is introduced in order not to change the after-embedding histogram excessively. The second one is a histogram preserving method based on histogram matching using two quantizers with a dead zone. In comparison with F5 as a representative JPEG steganography, the two methods show high performance with regard to embedding rate, PSNR of stego image, and particularly histogram preservation.

Colorization in YCbCr color space and its application to JPEG images

This paper presents a colorization method in YCbCr color space, which is based on the maximum a posteriori estimation of a color image given a monochrome image as is our previous method in RGB color space. The presented method in YCbCr space is much simpler than that in RGB space and requires much less computation time, while both methods in YCbCr and RGB space produce color images with comparable PSNR values. The proposed colorization in YCbCr is applied to JPEG compressed color images aiming at better recovery of downsampled chrominance planes. Experimental results show that colorization in YCbCr is usually effective for quality improvement of JPEG color images.

High capacity and secure digital steganography to palette-based images

We have already proposed a large capacity steganography for gray scale images called BPCS-steganography. This paper shows a method to apply BPCS-steganography to palette-based images which consists of a palette storing color vector information and an index image whose pixel value is corresponding to a index in the palette. A palette-based images can be represented by combining R G and B color component images. We embed secret information into the G images. A number of color vectors in a palette after embedding by BPCS would be over the maximum number. In order to reduce the number of colors, the rest of the two component images are then changed in a way that minimizes the square error. The idea behind the color quantization is that the degrading of images manipulated to reduce color is worse than the degrading which occurs with the embedding.

Steganography based on region segmentation with a complexity measure

This paper describes a new steganographic technique using image segmentation based on a local complexity measure. The key to this approach is that a binary image can be divided into “informative” and “noiselike” regions by using a “complexity measure.” This property allows us to embed secret data in the noiselike regions if the secret data have a random pattern. If the secret data are simple, then we apply an image conjugate operation that transforms a simple pattern into a complex pattern. In the experiment, a JPEG file was embedded into a gray scale dummy image (256 × 256, 8 bits/pixel) without losing any visual information.

Colorization in YCbCr Space and its Application to Improve Quality of JPEG Color Images

This paper presents a colorization method in YCbCr color space, which is based on the maximum a posteriori estimation of a color image given a monochrome image as is our previous method in RGB color space. The presented method in YCbCr space is much simpler than that in RGB space and requires much less computation time, while both methods in YCbCr and RGB space produce color images with comparable PSNR values. The proposed colorization in YCbCr is applied to JPEG compressed color images aiming at better recovery of down sampled chrominance planes. Experimental results show that colorization in YCbCr is usually effective for quality improvement of JPEG color images.

Bit-Plane Decomposition Steganography Combined with JPEG2000 Compression

This paper presents a steganography method based on JPEG2000 lossy compression scheme and bit-plane complexity segmentation (BPCS) steganography. In JPEG2000 compression, wavelet coefficients of an image are quantized into a bit-plane structure and therefore BPCS steganography can be applied in the wavelet domain. The proposed JPEG2000-BPCS steganography was implemented using JJ2000 Java software of JPEG2000 compression, with which the program module for BPCS steganography was integrated. The proposed steganography enables us to use JPEG2000 lossy compressed images as dummy files for embedding secret data. Embedding rates of around 15% of the compressed image size were achieved for pre-embedding 1.0bpp compressed images with no visually noticeable degradation in image quality.

Topological-ordered color table for BPCS-steganography using indexed color images

Image index tables values generally give the best possible representation of the color information of the image. However, no consideration is given to the arrangement of the color table itself. Thus, depending on the image, pixels with similar colors may have different index values and can therefore have considerably different index binary makeups. Consequently, regions of similarly colored indexed pixels can be noise-like at the bitplane level while the output colors themselves may imply simple bitplane patterns. BPCS image steganography hides information in images based on the principle that if regions in a bitplane are noise-like, those regions can be replaced with noise-like secret data. Therefore, applying traditional BPCS steganography to indexed image data results in drastic visible changes to the image. To overcome this problem, we used a self-organizing neural network to reorder the index table, based on samples from the image, such that similar colors in the index table are near each other with respect to their index values. As a result, regions with similar color information have only slight binary differences at the bitplane level, whereas regions with mixed color information will have considerable binary differences. Using this technique, we can embed secret data that is 15 to 35 percent the size of the image with little or no noticeable degradation in the image.