Abstract: Hyperspectral imaging has been widely studied in many applications; notably in climate changes, vegetation, and desert studies. However, such kind of imaging brings a huge amount of data, which requires transmission, processing, and storage resources for both airborne and spaceborne imaging. Compression of hyperspectral data cubes is an effective solution for these problems. Lossless compression of the hyperspectral data usually results in low compression ratio, which may not meet the available resources; on the other hand, lossy compression may give the desired ratio, but with a significant degradation effect on object identification performance of the hyperspectral data. Moreover, most hyperspectral data compression techniques exploit the similarities in spectral dimensions; which require bands reordering or regrouping, to make use of the spectral redundancy. In this paper, we analyze the spectral cross correlation between bands for AVIRIS and Hyperion hyperspectral data; spectral cross correlation matrix is calculated, analyzed, and by assessing the strength of the spectral matrix, we propose a new technique for bands regroup by finding the highly correlated groups of bands in the hyperspectral data cube based on "inter band correlation square".

Abstract: Tuberculosis (TB) is one of the primary cause of the death in the developing countries, certainly it is coming into lime light from various countries, either developed countries or developing countries. Sputum examination microscopically by using Ziehl-Neelsen stain (ZN-stain) method directly is a primary examination which is still used in all over the world included in Indonesia according to recommendation of the World Health Organization (WHO). Certainly this examination is depend on the expertise of the existing human resources and intensive examination time consuming. In the developing country with limited facility, a little number of expert, and not a cheap cost are some of the reason about how difficult to pressing the development of tubercular.
Therefore, it is needed an automation in TB bacteria examination from a digital image of ZN-stain sample which can press the examination cost, time required, and human error. In this research, the algorithm of image processing for identification of TB bacteria is developed by using neural network. The testing result by using 15 hidden layer is obtained accuracy about 88%.

Abstract: A new sub-image identification technique that does not need segmentation is presented. The sub-image identification is achieved by first, decomposing each database image into a set of 8×8 pixel patches covering the entire image. Finally, a collection of sub-images corresponding to different image regions and scales is obtained. This method is also used for extracting information about the relationship between each image with other images stored in the database. A method that enables the identification of original images even after rotation or flipping operations is proposed.

Abstract: In recent years, there has been significant development in multimedia technologies. Transmission of multimedia data such as audio, video and images over the Internet is now very common. The Internet, however, is a very insecure channel and this possess a number of security issues. To achieve confidentiality and security of multimedia data over an insecure channel like the Internet, a number of encryption schemes have been proposed. The need to develop new encryption schemes comes from the fact that traditional encryption schemes for textual data are not suitable for multimedia data stream. This paper presents a framework to evaluate image encryption schemes proposed in the literature. Instead of visual inspection, a number of parameters, for example, correlation coefficient, information entropy, compression friendliness, number of pixel change rate and unified average change intensity etc., are used, to quantify the quality of encrypted images. Encryption efficiency analysis and security evaluation of some conventional schemes like the Advanced Encryption Standard (AES) and Compression Friendly Encryption Scheme (CFES) is also presented. The security estimations of AES and CFES for digital images against brute-force, statistical, and differential attacks are explored. Experiments results are presented to test the security of these algorithms for digital images. After analysis of AES and CFES, some weaknesses have been discovered in CFES. These weaknesses were mainly related to low entropy and horizontal correlation in encrypted images.