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Infrared imagery is extensively used in defense, remote sensing and medical applications. While the infrared images have many advantages over RGB images, the details in these images are usually blurred which in turn leads to some difficulties for human operators. In this paper, a new method based on Laplacian of Gaussian scale-space and local variance is presented to improve the visual quality of the infrared images. At the first step, the Gaussian scale-space is constructed by convolving the original image with different Gaussian kernels. Then, the two-dimensional Laplacian kernels are convolved with the Gaussian scale-space to achieve details with both positive as well as negative contrasts. The weighted details are added to the original image to deblur the dim areas. At the final step, to increase the dynamic range of the image and have better visual quality, the local variance of the image is also added to the output of the previous step. Since finding optimum weighting coefficients is a difficult task empirically, here, we use a population-based meta-heuristic optimization algorithm called particle swarm optimization (PSO) to find the optimum values for weighting coefficient values. Beside qualitative comparison, Structural Similarity (SSIM) and second-derivative-like measure of enhancement (SDME) are used to quantitatively investigate the images quality. The proposed method outperforms the baseline algorithms in both qualitative and quantitative perspectives. [ABSTRACT FROM AUTHOR]

When designing a system-on-chip (SOC), a network-on-chip (NOC) paradigm is the backbone of used interconnection, but in recent years, with a great improvement in silicon technology and the ability to implement billions of transistors on a wafer, it sounds that wire-based communication is not efficient any longer, therefore designers intend to replace wireless transferring data methodology instead. In the following, we show how the performance of the wireless network is improved with subnet extension. This paper focuses on the evaluation of delay and throughput which are two important factors in network proficiency. In fact, to enhance the performance of the system, we need to reduce the number of delay cycles and improve the throughput, therefore to keep balance between these two parameters, designer has to adjust the packet injection rate (PIR) in a safe margin such that it does not exceed a certain point in each state, otherwise delay is uncontrollable, thus it is required to clearly identify the take-off points. About the designer also has to be informed purpose for which the system is going to be designed. It strictly depends on whether high throughput or low delay cycle is desirable. Subnet extension is a way to achieve this target. Here, totally three networks with the number of cores 64, 512 and 1024 have been selected, respectively. The effect of subnet extension is evaluated on each one. The behavior of each network with different number of subnets and IPs is studied. Obtained results from the simulator for different ranges of PIR and subnets are significant. To emphasize, we highlight the take-off points for the delay cycles and the points which does not cross the PIR level. Performance evaluation is conducted based on flit-accurate and open source system C simulator BookSim. [ABSTRACT FROM AUTHOR]