Shigeo Kato

Image coding using concentration and dilution based on seam carving with hierarchical search

Image concentration is an image resizing technique which shrinks an image size but does not change important region(s) in the original image, whereas image dilution is the reverse process to image concentration. In this paper, we incorporate image concentration/dilution process in image coding. An image retargeting method called seam carving is used for image concentration. Furthermore, it is modified to yield rate-distortion optimized seams by a hierarchical search process. Our method can be incorporated into any image encoder since the image concentration (dilution) is a pre(post)- processing of image encoder (decoder). In the experimental results, JPEG/SPIHT with image concentration/dilution presents significant bitrate savings compared with the original JPEG/SPIHT alone and reconstructed image qualities are very similar to each other.

Adaptive Directional Wavelet Transform Based on Directional Prefiltering

This paper proposes an efficient approach for adaptive directional wavelet transform (WT) based on directional prefiltering. Although the adaptive directional WT is able to transform an image along diagonal orientations as well as traditional horizontal and vertical directions, it sacrifices computation speed for good image coding performance. We present two efficient methods to find the best transform directions by prefiltering using 2-D filter bank or 1-D directional WT along two fixed directions. The proposed direction calculation methods achieve comparable image coding performance comparing to the conventional one with less complexity. Furthermore, transform direction data of the proposed method can be used for content-based image retrieval to increase retrieval ratio.

Improved image concentration for artifact-free image dilution and its application to image coding

In this paper, an improved method of image concentration for image coding with concentration and dilution is presented. Image concentration is an image resizing technique which shrinks an image size but does not change important region(s) in the original image, whereas image dilution is the reverse process to image concentration. The authors have proposed an image coding approach based on the image concentration and dilution. This paper focuses on an improvement of image concentration to enhance quality of the reconstructed (diluted) image. In the experimental results, the improved method obtains bitrate savings compared with image encoders alone, and the reconstructed images do not have perceptually noticeable artifacts.

A study on an image synthesis method for graphical passwords

In this paper, we present an image synthesis method for graphical passwords. Graphical passwords are an authentication method that uses pictures as passwords instead of using alphanumeric characters. However, they are usually easy to memorize for not only users but also observers or attackers who stand behind the users. In our method, we combine low frequency components of a decoy picture with high frequency components of a pass-picture. This makes it difficult for observers to recognize the pass-image.

Seam carving with rate-dependent seam path information

In this paper, we present a seam carving, which is a well-known content-aware image resizing method, with a constraint on bitrates for seam path information (SPI). The SPI corresponds to pixel positions to be pruned and it generally requires high bitrate when we store or transmit it. However, the SPI should be transmitted to receivers in the case that the receivers are devices with low computing power, such as cell phones and PDAs since seam carving at the receivers is a computationally-demanding process. We resolve the problem by applying piecewise linear approximation to the seam paths. In the experimental results, the retargeted images yielded by the original seam carving and the proposed one are very similar, whereas required bitrate for the SPI in the proposed method is 34–97 % less than the original one.

Rate-dependent seam carving and its application to content-aware image coding

Content-aware image resizing (CAIR) is desired because it preserves prominent regions in a resized image. However, CAIR requires high computational complexity to perform in mobile devices, though it is desired for these displays. Moreover, transmitting the side information for CAIR from the encoder is a problem since it usually requires high bitrates compared with those for image data. In this paper, we present a rate-dependent CAIR method that produce various retargeting results based on the bitrates for side information. Furthermore, we apply the proposed technique to wavelet-based image coding. Our proposed content-aware image coding method provides good performances for both CAIR and image coding.

Digital image watermarking method using between-class variance

We propose a low-complexity, pixel-based watermarking method utilizing the edge areas in an image. In this method, an image is divided into blocks and the blocks are classified as edge blocks and non-edge blocks. The histogram of pixels in an edge block is a bi-modal distribution which has two peaks. Therefore, these pixels are further classified into two classes named “high peak class” and “low peak class”. Then, a bit of the watermark is embedded by controlling the between-class variance by changing the pixel values in each class of the edge block. We utilized the discriminant analysis method for deciding a threshold and controlling the between-class variance. The proposed method can improve the image quality while maintaining robustness against compression and smoothing. In this paper, we evaluated the image quality of watermarked images using PSNR and SSIM. We also evaluated robustness against JPEG compression and Gaussian filtering.

Highpass-filtering based adaptive directional wavelet transform

In this paper, a calculation method of transform directions for adaptive directional wavelet transform (AD WT) is proposed. It uses 2-D highpass filters as a preprocessing of the conventional calculation stage. The filters can reduce the number of direction candidates effectively. In image coding, our proposed framework shows very comparable results to the conventional AD WT and outperforms the traditional separable WT.

Wavelet-based content-aware image coding with rate-dependent seam carving

This paper proposes an image coding method incorporated with content-aware image resizing. It is a promising application of our previously proposed rate-dependent seam carving (RD-SC). RD-SC is combined with lifting-based discrete wavelet transform to construct a new multiresolution image representation. Furthermore, the modified parent-children relationship of SPIHT is shown. Our proposed image coding presents comparable performances to the conventional SPIHT even for the original size, and retargeted image quality is satisfactory.

Adaptive color-to-gray image mapping using directional transform

Several color-to-gray mapping methods were proposed to restore a color image from its corresponding grayscale image. These methods are based on embedding chrominance signals into high-frequency subbands of the luminance signal. In the conventional methods, only separable filters are used for the subband decomposition. In addition, subbands at fixed positions are always used to embed chrominance signals. However, in many images, diagonal components are included as well as horizontal/vertical ones. Therefore, qualities of chrominance-embedded grayscale and restored color images are sometimes degraded especially for images with rich textures. In this paper, we propose an improved color restoration method using a directional transform named hybrid wavelets and directional filter banks which considers directionality in images. Experimental results show our method improves the image qualities of the restored color images as well as the chrominance-embedded grayscale images.