Background and Objectives: Depth from defocus and defocus deblurring from a single Image are two challenging problems caused by the finite depth of field in conventional cameras. Coded aperture imaging is a branch of computational imaging, which is used to overcome these two problems. Up to now, different methods have been proposed for improving the results of either defocus deblurring or depth estimation. In this paper, an asymmetric coded aperture is proposed which improves results of depth estimation and defocus deblurring from a single input Image.Methods: To this aim, a multi-objective optimization function taking into consideration both deblurring results and depth discrimination ability is proposed. Since aperture throughput affects on Image quality, our optimization function is defined based on illumination conditions and camera specifications which yields an optimized throughput aperture. Because the designed pattern is asymmetric, defocused objects on two sides of the focal plane can be distinguished. Depth estimation is performed using a new algorithm, which is based on perceptual Image quality assessment criteria and can discern blurred objects lying in front or behind the focal plane.Results: Extensive simulations as well as experiments on a variety of real scenes are conducted to compare the performance of our aperture with previously proposed ones.Conclusion: Our aperture has been designed for indoor illumination settings. However, the proposed method can be utilized for designing and evaluating appropriate aperture patterns for different imaging conditions.

A conventional camera with small size pixels may capture Images with defocused blurred regions. Blurring, as a low-pass filter, attenuates or drops details of the captured Image. This fact makes deblurring as an ill-posed problem. Coded aperture photography can decrease destructive effects of blurring in defocused Images. Hence, in this case, aperture patterns are designed or evaluated based on the manner of reduction of these effects. In this paper, a new function is presented that is applied for evaluating the aperture patterns which are designed for defocus deblurring. The proposed function consists of a weighted sum of two new criteria, which are defined based on spectral characteristics of an aperture pattern. On the basis of these criteria, a pattern whose spectral properties are more similar to a flat all-pass filter is assessed as a better pattern. The weights of these criteria are determined by a learning approach. An aggregate Image quality assessment measure, including an existing perceptual metric and an objective metric, is used for determining the weights. According to the proposed evaluation function, a genetic algorithm that converges to a near-optimal binary aperture pattern is developed. In consequence, an asymmetric and a semi-symmetric pattern are proposed. The resulting patterns are compared with the circular aperture and some other patterns in different scenarios.

Nowadays, one of the most important issues in the field of Image processing is Image de-blurring. De-blurring of an Image can be achieved via two different approaches; blind de-blurring and non-blind de-blurring. In blind de-blurring, the kernel by which the blur has occurred is assumed unknown, while in non-blind de-blurring, this kernel is given. In blind de-blurring, the blurring kernel must be estimated in order to sharpen the corrupted Image. This may increase the computational cost of the de-blurring process. Non-blind Image de-blurring is an ill-posed problem with linear reverse issues. Therefore, we develop optimization problems in order to estimate the original sharp Images. Usually, non-blind de-blurring methods assume that the blurring kernel is error-free, however, in practice our knowledge of the PSF is uncertain. Hence, in this paper, we use a semi-blind method for de-blurring the blurred Image that is robust to this uncertainty. The proposed robust optimization model is followed by a filter for Image de-blurring that can attain the solution with lowest possible error in the worst case scenarios, that is, the maximum uncertainty about the blurring kernel. Based on the simulation results, our proposed semi-blind model yields more than 4 dB PSNR improvements compared to conventional blind Image de-blurring methods.

Purpose: The study purpose was to determine and compare the Recall and Precision of Bing and Google Image search engines for content based Image retrieval. Methodology: The research used webometrics and comparative methods. Population includes Images stored in the databases of Bing and Google search engines, and research sample includes 15 selective Images searched in any of search engines. All the retrieved sources through the Images by Image content based Image search were gathered, results’ Recall and Precision measures were calculated by relevance formula and their average percentage were obtained. Research hypotheses were tested by U Mann-Whitney test as well. Findings: Findings showed that the Google search engine functionality was higher with recall measure of % 88. 73 than recall rate (%20. 86) for Bing. But Bing search engine had higher precision (% 99. 86) than Google (%94. 80). Results: Hypotheses tests on recall and precision in two search engines’ Image retrieval showed a significant difference for recall in favor of Google, indicating its better functionality than Bing but there was no significant difference between them concerning precision since both showed fair precision however Bing was relatively useful.

In this paper, an alternative approach in operational modal analysis is presented, utilizing Image processing technique and transmissibility functions. Imaging sensors do not impose additional mass on the structure due to their non-contact nature, while transmissibility functions, independent of excitation type, can directly extract mode shapes. The innovation of this research lies in combining these two techniques to record dynamic responses and identify modal properties. To capture the temporal response history from video signals, the block-matching method with sub-pixel accuracy was employed. Validation was conducted by recording the response of the tip of a cantilevered steel beam subjected to impact excitation, using a high-speed camera and a laser vibrometer, simultaneously. The RMSE plots in the time domain and the PSD in the frequency domain indicate high accuracy of this method. Using this approach, the displacement time histories of various points on the structure were extracted from the video signals, and the modal properties, including natural frequencies, damping ratios, and mode shapes, were identified using the transmissibility matrix method. The results obtained from the proposed method were compared with the stochastic subspace identification (SSI) method and analytical solutions. The findings reveal the accuracy of the modal identification approach introduced in this article. The highest relative error in estimating the natural frequencies of the first and second modes, compared to the values from the laser method, are 0.19% and 0.13%, respectively, and in comparison to the analytical values, they are 0.34% and 1.5%, respectively.

In Kant and the Problem of Metaphysics (KPM), Heidegger shows how the initial Image-making power of the imagination is pictorial in the pure Image of time. He further clarifies the recognized link between the syntheses and the time-visualizing power of Images which is pictorial formative power, which can visualize time. The three syntheses of imagination are replaced with the modes of existence of Dasein. Three kinds of photographs resemble the Images produced when the transcendental imagination functions as Dasein. We can address the ways to visualize time by considering Dasein with a photographic preoccupation through 1. A possible look in the form of presentation (a photograph shows an immediate look of a house or person as intuitable this-here); 2. An immediate look of the thing, house, or deceased person, as well as a copy or its reproduction as a death mask; and, 3. The manner of contemplation of a likeness is an immediate look of a being present in the form of representation.