Papers by Keyword: Super Resolution

Abstract: In this paper, we propose a new super-resolution algorithm based on wavelet coefficient. The proposed algorithm uses discrete wavelet transform (DWT) to decompose the input low-resolution image sequences into four subband images, including LL, LH, HL, HH. Then the input images have been processed by the 3DSKR (Three Dimensional Steering Kernel Regression) super resolution (SR) algorithm, and the result replaces the LL subband image, while the three high-frequency subband images have been interpolated. Finally, combining all these images to generate a new high-resolution image by using inverse DWT. Proposed method has been verified on Calendar and Foliage by Matlab software platform. The peak signal-to-noise (PSNR), structural similarity (SSIM) and visual results are compared, and show that the computational complexity of the proposed algorithm decline by 30 percent compared with the existing algorithm to obtain the approximate results.

Abstract: This article introduces several interpolation algorithms, and analyze the characteristic and disadvantage of wavelet transformation and contourlet transformation. A Bi-cubic interpolation algorithm based on non-subsampled contourlet transformation is described. The experiments prove this algorithm can improve the quality of image reconstruction better than Bi-cubic interpolation, wavelet bi-cubic interpolation and contourlet interpolation.

Abstract: A framework is proposed to reconstruct a super resolution image from a single low resolution image with Gaussian noise. The degrading processes of Gaussian blur, down-sampling, and Gaussian noise are all considered. For the low resolution image, the Gaussian noise is reduced through Wiener filtering algorithm. For the de-noised low resolution image, iterative back projection algorithm is used to reconstruct a super resolution image. Experiments show that de-noising plays an important part in single-image super resolution reconstruction. In the super reconstructed image, the Gaussian noise is reduced effectively and the peak signal to noise ratio (PSNR) is increased.

Abstract: In order to improve the resolution of single image with Pepper and Salt noise, a framework is proposed. In the low resolution imaging model, the Gaussian blur, down-sampling, as well as Pepper and Salt noise are considered. For the low resolution image, the Pepper and Salt noise is reduced through median filtering method. Super resolution reconstruction is performed on the de-noised low resolution image by iterative back projection algorithm. Experimental results show that the Pepper and Salt noise are removed effectively and the peak signal to noise ratio (PSNR) of the super resolution reconstructed image is improved.

Abstract: The 2D spectrum estimation based on uniform linear array is studied in this paper. MUSIC method is firstly introduced into array signal processing to realize the frequency and angle joint estimation. And the modified MUSIC method is then applied for two dim array signal processing to fulfill joint parameters estimation of coherent signal sources. Simulation results show the validity of the proposed method. Keywords: Super resolution;Array signal processing;Parameter estimation;MUSIC algorithm

Abstract: In a variety of practical microscopic imaging applications, many industries require not only lateral resolution improvement but also axial resolution improvement. The resolution in optical microscopy is limited by diffraction and determined by the wavelength of the incident light and the numerical aperture (NA) of the objective lens. The diffraction limit is mathematically described by a point spread function in the imaging system, and three-dimensional (3D) point spread functions describe both the lateral and axial resolutions. Thus, it is useful to focus on exceeding this limit and improving the resolution of optical imaging by the spatial control of structured illumination. Structured illumination microscopy is a familiar technique to improve resolution in fluorescent imaging, and it is expected to be applied to industrial applications. Microscopic imaging is convenient, non-destructive, and has a high-throughput performance and compatibility with a number of applications. However, the spatial resolution of conventional light microscopy is limited to wavelength scale and the depth of field is shallow; hence, it is difficult to obtain detailed 3D spatial data of the object to be measured. Here, we propose a new technique for generating and controlling wide-field 3D structured illumination. The technique, based on the 3D interference of multiple laser beams, provides lateral and axial resolution improvement, and a wide 3D field of view. The spatial configuration of the beams was theoretically examined and the optimal incident angle of the multiple beams was confirmed. Numerical simulations using the finite difference time domain (FDTD) method were carried out and confirmed the generation of 3D structured illumination and spatial control of the illumination by using the phase shift of incident beams.

Abstract: In this paper, we propose a new super resolution (SR) reconstruction method to handle license plate numbers of vehicles in real traffic videos. Recently, SR reconstruction shemes based on regularization have been demonstrated to be effective because SR reconstrction is an ill-posed problem. Working within this promising framework, the residual data (RD) term can be weighted according to the differences among the observed LR images in the SR reconstruction model. Moreover, L₁ norm is used to measure the RD term in order to improve the robustness of our method. Experiments show the proposed method improves the subjective visual quality of the high resolution images.

Abstract: This paper presents the resent advances in our research on ultrahigh resolution laser confocal microscopy to further improve the accuracy of non-contact 3D measurement of micro-structural dimensions and profiles at the level of micron/nanometer with emphasis on ways and means to improve axial and lateral resolutions. A scan measuring technique based on differential confocal microscopy is developed using the difference in the distribution of the scanning spot on near and far confocal planes by keeping the detectors off-focus at equal distance before and after the conjugate image plane of the scanning spot. This differential confocal microscopic scan measuring technique can be used to double the measurement sensitivity and obviously expand the linear range to improve the axial resolution, and to locate the tracking zero point at the center of the linear range with the highest sensitivity to achieve the bipolar tracking properties. In addition, this new technique can be used to effectively suppress the light source intensity drift and detector electronic drift and noise to improve the S/N ratio. The differential confocal detection technique can be combined with the optical superresolving filtering technique to improve both lateral and axial resolutions, and the confocal detection technique based on micro optical arrays has a very promising potential application for improving of detection efficiency.