Taking into account the lack of prior-information on account of single image, we design a image super-resolution reconstruction method, based on the possibility and the theory basis of the single image super-resolution reconstruction. Analysis of the process of the algorithm is also included. Because the theory and method of Markov random field are being developed constantly, the theory and method may described the part statistic of the image. The paper analyses the image super resolution reconstruction based on Markov Random Field, this apply the image super resolution processing. This presented a super resolution reconstruction technique based on wavelet decomposition and Markov Random Field, and has carried on the experimental research. Experiment result proves that the super resolution processing method on the basis of the Markov random field (MRF) can obtain the good super resolution restoration processing result.
In the research of super resolution reconstruction based on a set of images, we put emphases on analyzing the algorithm of super resolution based on multi-frame image or image set, i.e. how to reconstruct super resolution image using several low resolution images and under-sampled images. Discussion on recursively iteration reconstruct super resolution image is carried out, under both cases with noise and without noise. In this paper we bring Kalman filter theory into image super resolution rebuilding algorithm, make use of Kalman filter to go on a movement estimation to sequence image, and present a kind of simplified image super resolution reconstruction algorithm based on recursion iterative movement estimation of Kalman filte, and analyze this method. Then we make use of advanced method to test standard sequence image and acquired sequence image by shooting, and get a good result.
The paper presents the approach of image super-resolution reconstruction based on genetic algorithm. We use genetic algorithm as an optimizing tool, considering the image set as initial population, and thus establish an algorithm based on genetic algorithm aiming at image super-resolution reconstruction. Simulating experiments have been carried out, which proves that the algorithm we put forward can enhance the resolution and quality of the image and the result is satisfactory.
Based on lifting scheme and the construction theorem of the integer Haar wavelet and biorthogonal wavelet, we propose a new integer wavelet transform construct method on the basis of lift scheme after introduciton of constructing specific-demand biorthogonal wavelet transform using Harr wavelet and Lazy wavelet. In this paper, we represent the method and algorithm of the lifting scheme, and we also give mathematical formulation on this method and experimental results as well.
According to characteristic of image wavelet transform and interpolation, this paper proposes a remote sensing image interpolation method combining wavelet transform and interpolation algorithm, which can improve the remote sensing image resolution. Experiments show that the algorithm can properly retain abundant high frequency information in original remote sensing image. After interpolation processing and wavelet reconstruction, we can obtain a remote sensing image with higher resolution, better visual effect, higher Signal Noise Ratio (SNR), more detail information and no apparent warp. Therefore, this algorithm is an effective method of super-resolution remote sensing image processing.
In this paper, a new method is proposed to hide watermark image based on the discrete integer Haar wavelet transform. This method utilizes excellent properties of the discrete integer Haar wavelet transform and some characteristics of human visual system(HSV). The watermark are processed the discrete Haar wavelet transforms as a grey-value image, and are decomposed and synthesized the image of the watermark and hiding. The algorithm of the discrete integer Haar wavelet is simple and viable. Algorithmic operation is also small .The speed of algorithmic operation is quick. The algorithm is of parallel structure. The experimental results using this algorithm shows that the method of this paper implement that be added watermark and be hidden processing to image. This method can improve robustness of watermarking.
KEYWORDS: Video, Image compression, Wavelets, Video coding, Video compression, Video surveillance, Multimedia, Image segmentation, 3D modeling, Computer programming
This paper presents a novel compression encoding/decoding method based on lift scheme for I-VOP. In traditional coding I-VOP algorithm, the textures and shapes are separately coded, and the macro-block DCT coding method is adopted in the coding texture and 16x16 BAB(Binary Alpha Block) coding method is employed in shape coding. The texture and shape coding method is not of embed feature. The algorithm based on lift scheme for I-VOP, the texture and shape at same time is coded and the bit streaming is of embed feature.
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