In this paper, we propose a novel data hiding algorithm for high dynamic range (HDR) images encoded by the OpenEXR file format. The proposed algorithm exploits each of three 10-bit mantissa fields as an embedding unit in order to conceal k bits of a secret message using an optimal base which produces the least pixel variation. An aggressive bit encoding and decomposition scheme is recommended, which offers a high probability to convey (k + 1) bits without increasing the pixel variation caused by message concealment. In addition, we present a bit inversion embedding strategy to further increase the capacities when the probability of appearance of secret bit “1” is greater than 0.5. Furthermore, we introduce an adaptive data hiding approach for concealing more secret messages in pixels with low luminance, exploiting the features of the human visual system to achieve luminance-aware adaptive data hiding. The stego HDR images produced by our algorithm coincide with the HDR image file format, causing no suspicion from malicious eavesdroppers. The generated stego HDR images and their tone-mapped low dynamic range (LDR) images reveal no perceptual differences when subjected to quantitative testing by visual difference predictor. Our algorithm can resist steganalytic attacks from the HDR and LDR RS and SPAM steganalyzers. We present the first data hiding algorithm for OpenEXR HDR images offering a high embedding rate and producing high visual quality of the stego images. Our algorithm outperforms the current state-of-the-art works.

In the era of information explosion, the traditional approach to storing data have faced challenges due to the rapid growth of information. It becomes an important issue when we come to processing the large dataset and trying to retrieve the useful information from a big database. This paper presents an effective scheme which employs hybrid cache architecture on the existing database system to enhance the query performance without increasing the hardware cost. Our scheme can be applied to satisfy the traditional database query over the Internet. The experimental results collected from a practical application show that the data query can be speeded up to 26 times. Performance evaluation shows that the response time of queries is less than 0.02 seconds when the query hits the shared memory cache. The proposed architecture can be easily applied to the traditional SQL database to accelerate the database query without significant programing efforts.

Linear interpolation is a simple yet effective technique for image composition which works wells for low dynamic range (LDR) images with a fixed range of pixel values. However, it cannot provide good performance for high dynamic range (HDR) images because a high luminance image usually dominates the composition result. This paper proposes a novel algorithm for HDR composition using the linear interpolation. Our scheme decomposes HDR images to be composed into three layers where a linear interpolation can be applied on each layer individually that has been normalized. The algorithm contains three steps including the image decomposition, the image feature composition, and finally the HDR map estimation and image re-rendering. Experimental results show that the proposed approach can produce informative HDR composition images balancing the influence caused by the low or high luminance and preserving the contrast, colors, and salience. The comparison demonstrates that our scheme outperforms the current state-of-the-art methods.

Random unique number generator can be used for generating a series of unpredictable and unrepeatable numbers within limited ranges of data and numbers. These numbers are usually distributed equally, random, independent, unpredictable and unrepeatable. A good random number generator has to be effective for a long period and has good statistical distribution and efficient generating performance. This study proposes a computational methodology to generate pseudo-random numbers based on random base polynomial, which uses less memory but generates a great deal of unrepeated pseudo-random numbers. Then this method adopts the multi-thread parallelization to effectively get the benefits of multi-core processors to accelerate the generation of a huge amount of pseudo-random numbers.