2D Wavelet Tree Ordering Based Localized Total Variation Model for Efficient Image Restoration

The degraded image during the process of image analysis needs more number of iterations to restore it. These iterations take long waiting time and slow scanning, resulting in inefficient image restoration. A few numbers of measurements are enough to recuperate an image with good condition. Due to tree sparsity, a 2D wavelet tree reduces the number of coefficients and iterations to restore the degraded image. All the wavelet coefficients are extracted with overlaps as low and high sub-band space and ordered them such that they are decomposed in the tree ordering structured path. Some articles have addressed the problems with tree sparsity and total variation (TV), but few authors endorsed the benefits of tree sparsity. In this paper, a spatial variation regularization algorithm based on tree order is implemented to change the window size and variation estimators to reduce the loss of image information and to solve the problem of image smoothing operation. The acceptance rate of the tree-structured path relies on local variation estimators to regularize the performance parameters and update them to restore the image. For this, the Localized Total Variation (LTV) method is proposed and implemented on a 2D wavelet tree ordering structured path based on the proposed image smooth adjustment scheme. In the end, a reliable reordering algorithm proposed to reorder the set of pixels and to increase the reliability of the restored image. Simulation results clearly show that the proposed method improved the performance compared to existing methods of image restoration.

Calculation of contrast for computer simulated resolution chart image

The work is devoted to the analysis of the resolution chart image created with the Image Simulation mode of ZEMAX software. The changes in image quality are simulated using the model of Helios-44M-4 photographic objective lens. The research is conducted for monochromatic light conditions and computer simulated resolution test chart as an object for the lens with different chart positions. An axial beam and an off-axis beam that corresponds to the maximum object space field angle are analyzed. The calculation of contrast of the simulated resolution chart images is made modeling different spatial frequencies of the chart lines. The contrast is calculated in three ways. The first way uses the maximum and minimum values of the image illumination, and the second and third ways are based on the integral values of the illumination of black and white lines, calculated with the method of rectangles and the method of trapeziums, respectively. Having been calculated the values of contrast are compared with the theoretical values of the diffraction modulation transfer function obtained with ZEMAX.