No abstract

In this study, a modified curve fitting model (CFM) for cylindrical dielectric resonator antenna (DRA) exclusively using YIG resonator with excess Fe2O3 is proposed. The modified CFM is used to accelerate the analysis of YIG resonator antenna (YRA) without having to repeat the characterization process for similar resonator. Modification of CFM is done using least square method in which correlation and regression analyses are used. The modified equations of resonant frequency and Q‐factor are adapted for the YRA design using YIG resonator with excess Fe2O3 of 9%. Comparison between the simulation, measurement, and modified CFM results are very well matched.

No abstract

Microscopy lens distortion will cause errors during parasites image acquisition for water sample inspection. Since water sample inspection is crucial for treated water monitoring, the quality of microscopic parasite images such as Giardia and Cryptosporidium need to be monitored as well to avoid errors in treated water inspection. In this work, the subjective and objective evaluation of parasite images were performed. The parasite species studied were Cryptosporidium and Giardia (oo)cysts. Parasite image database consisting of 20 reference images and 360 distorted images were used in the evaluation. The distorted images were generated from the reference images by applying distortion to the reference images with Gaussian White Noise and Motion Blur, at 9 levels of distortions. Twenty subjects were selected to assess the distorted images for the subjective evaluation. The scores obtained from the subjects were transformed into Mean Opinion Score (MOS). In the objective evaluation, six Full Reference-IQA (FR-IQA) metrics, namely MSSIM, SSIM, FSIM, IWSSIM, GMSD and VIF were used to evaluate the distorted images. The subjective MOS scores were used as the benchmark to determine the most suitable objective IQA to assess parasite images. The relationship between the subjective MOS and objective IQAs are examined using performance metrics namely PLCC and RMSE. It was found that MSSIM is the most suitable IQA to assess parasite images distorted with Gaussian White Noise and Motion Blur.

In this paper, we perform an automatic correction of luminosity and contrast of retina images. One hundred retina images with varying level of reflectance taken from custom and online databases are used to test the effectiveness of the proposed method. The approach is implemented in 4 stages namely pre-processing, lowpass filtering, luminosity equalization, and contrast stretching. In the pre-processing stage, the three components of a color retina image are separated and only the green channel is processed further as it contains the most information. Then the region of interest (which is the eye region) and its border are marked. After that, the eye region (ROI) of the green channel is subjected to lowpass filtering, row by row to create a smooth background luminosity surface without the foreground objects like the optic disc, exudates, blood vessels and blood spots. Three different types of lowpass filters are used and their performances are compared. The resulting background luminosity surface allows the estimation of the background illumination. Then, based on the background surface, the luminosity of the ROI is equalized so that every pixel experiences the same brightness. Finally, the contrast of the ROI is improved by histogram stretching so that the foreground objects appear more clearly. The proposed method was implemented using MATLAB R2021b running on AMD 5900HS processor and the average execution time was less than 1 second. The execution time can be further reduced if the codes are optimized and GPU is used. Overall, the proposed method improves the luminosity and contrast of the images greatly. This technique can be a useful tool to ophthalmologists who perform visual inspection of microaneurysm, exudates and other lesions.