Abstract-Medical image processing is used for the diagnosis of diseases by the physicians or radiologists. Noise is introduced to the medical images due to various factors in medical imaging. Noise corrupts the medical images and the quality of the images degrades. This degradation includes suppression of edges, structural details, blurring boundaries etc. To diagnose diseases edge and details preservation are very important. Medical image denoising can help the physicians to diagnose the diseases. Medical images include MRI, CT scan, x-ray images, ultrasound images etc. In this paper we implemented bilateral filtering for medical image denoising. Its formulation & implementation are easy but the performance of bilateral filter depends upon its parameter. Therefore for obtaining the optimum result parameter must be estimated. We have applied bilateral filtering on medical images which are corrupted by additive white Gaussian noise with different values of variances. It is a nonlinear and local technique that preserves the features while smoothing the images. It removes the additive white Gaussian noise effectively but its performance is poor in removing salt and pepper noise.

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This research involves the implementation of a dual-input DC-DC boost converter for integrating solar and fuel cell energy sources with a smart grid. The growing demand for renewable energy sources necessitates the efficient utilization and integration of multiple energy systems. The proposed dual-input converter enables simultaneous extraction and management of power from solar panels and fuel cells, resulting in improved energy generation and utilization. The converter incorporates a smart grid interface, allowing bidirectional power flow between the energy sources and the grid. The design and control strategy of the dual-input converter are discussed in detail, with a focus on achieving high conversion efficiency, maximum power point tracking, and optimal power sharing between the solar panels and fuel cells. The control algorithm utilizes a combination of Perturb and Observe (P&O) and Incremental Conductance (IncCond) methods for Maximum Power Point Tracking (MPPT), ensuring efficient power extraction from the solar panels. Additionally, a Proportional-Integral (PI) controller is implemented to regulate power flow between the energy sources and the grid. Simulation and experimental results are presented to validate the proposed converter's performance under various operating conditions.

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