Showing papers by "Nagaaki Ohyama published in 2011"

Multispectral image enhancement for effective visualization.

Abstract: Color enhancement of multispectral images is useful to visualize the image’s spectral features. Previously, a color enhancement method, which enhances the feature of a specified spectral band without changing the average color distribution, was proposed. However, sometimes the enhanced features are indiscernible or invisible, especially when the enhanced spectrum lies outside the visible range. In this paper, we extended the conventional method for more effective visualization of the spectral features both in visible range and non-visible range. In the proposed method, the user specifies both the spectral band for extracting the spectral feature and the color for visualization respectively, so that the spectral feature is enhanced with arbitrary color. The proposed color enhancement method was applied to different types of multispectral images where its effectiveness to visualize spectral features was verified.

Lossless and lossy coding for multispectral image based on sRGB standard and residual components

Abstract: In this paper, we present a multispectral image (MSI) compression method using a lossless and lossy coding scheme, which focuses on the seamless coding of the RGB bit stream to enhance the usability of the MSI. The proposed method divides the MSI data into two components: RGB and residual. The RGB component is extracted from the MSI by using the XYZ color matching functions, a color conversion matrix, and a gamma curve. The original MSI is estimated by an RGB data encoder and the difference between the original and the estimated MSI, which is referred to as the residual component in this paper. Next, the RGB and residual components are encoded by using JPEG2000, and progressive decoding is achieved from the losslessly encoded code stream. Experimental results show that a high-quality RGB image can be obtained at a low bit rate with primary encoding of the RGB component. In addition, by using the proposed method, the quality of a spectrum can be improved by decoding the residual data, and the quality is comparable to that obtained by using JPEG2000. The lossless compression ratio obtained by using this method is also similar to that obtained by using JPEG2000 with the integer Karhunen-Loeve transform.

Class-based spectral reconstruction based on unmixing of low-resolution spectral information

Abstract: This paper proposes a class-based spectral estimation method for high-resolution red, green, and blue (RGB) images and corresponding low-resolution spectral data. Each spectrum in the low-resolution data is assumed to be a mixture of spectra of different classes. Then, the spectral estimation matrix for every class is derived using a regression approach, in which the clustering results of the high-resolution RGB image are used to incorporate spectral unmixing. Experiments confirm reduced normalized root mean squared error for the spectral images if the number of classes in the clustering is appropriately selected. In addition, the experimental results show that the spectra are accurately reconstructed even when they are observed as mixed spectra in the low-resolution data.

Quantitative analysis on key estimation by known-plaintext attacks to DRPE

Abstract: Double Random Phase Encoding (DRPE), which is a typical optical encryption technique, has been reported to be vulnerable to Known Plaintext-Attacks (KPAs) using a Phase Retrieval Algorithm (PRA). But the reported case in which the encryption key is successfully estimated was that the plain image was rather simple such as the image of a character. In addition, although Phase Only DRPE (PO-DRPE) was proposed to achieve more resistance to the KPA than Complex DRPE (C-DRPE) in which both amplitude and phase components are used as an encrypted image, no quantitative results about the relationship between the vulnerability and the plaintext image. In this paper, we show the result of quantitative analysis on KPA by PRA to C-DRPE and PO-DRPE, for the plaintext images of different characteristics. As a result of experiment, KPA to C-DRPE succeeded to estimate the correct key while the probability of success became lower when the number of non-zero pixel increases in the plaintext image. However, KPA to PO-DRPE enabled to estimate only "singular" keys, which are effective for no more than given plaintext/ciphertext image pair and far different from the correct encryption key. We also conducted KPA using two plaintext-ciphertext image pairs for KPA. In the case when two plaintext-ciphertext image pairs were given to KPA, the cryptanalysis succeeded with higher probability than the case of one. Moreover, the probability of success in the KPA was high even in PO-DRPE.

The development of a prototype e-p.o. box and its application to personal health information management system

Abstract: We introduce e-Post Office Box system which renders individuals their personal information management and safe access through the Internet to share and utilize their personal information under their own control. We have developed a personal health information management system based on the e-P.O.Box conception. All the personal information dealt in the system is securely protected in the network complying with the government guidelines for safety management of medical information systems. The system is connected with medical institutions using on-demand VPN and, the access to it is securely guarded by the use of IC card. We conducted a field experiment for the evaluation of the developed system with the staffs of Tokyo Institute of Technology and doctors in a hospital, simulating the cases of clinical consultation of patients with some adult disease. The experiment confirmed the effectiveness of the system for the patients.

Layered scalable coding of multispectral images based on visible component separation

Abstract: This paper presents multispectral image coding methods based on visible component separation techniques. By coding the visible components separately from other spectral components, the color information can be used without decoding the whole multispectral image. Two types of separation techniques are introduced: one is a direct separation of visible and invisible layers, while the other is a scalable separation. In the scalable separation, visible components are first compressed to produce the base layer bitstream. The enhancement layer data include not only invisible components but also the information on the distortion of the coded visible components. Such a separation technique improves the accuracy of decoded multispectral images especially when visible components are highly compressed. The performance of the proposed methods was evaluated for different bit allocations to visible components. In general, the coding performance reduces when data are divided and coded separately to incorporate scalabilities. Nonetheless, it is found that the proposed scalable approach realizes a peak signal-to-noise ratio PSNR value comparable to that achieved by employing JPEG2000, which incorporates no scalability.