Enhancement of Brain MRI Images Using Analog Filters and Pole-Zero Placement Methods

Image enhancement has a very crucial role in upgrading the visual quality and interpretability of digital images. In this study, we emphasize on the application of the Butterworth filter based on two different design techniques, namely analog filter design and pole-zero placement method for enhancing the MRI images. Several evaluation metrics are employed, including mean squared error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index (SSIM), for evaluating the performance of the Butterworth filter. These metrics provide quantitative measures of the image enhancement quality and allow for comparison with other enhancement techniques. The Butterworth filter’s parameters, such as the cut-off frequency and filter order, are carefully selected to achieve optimal enhancement results. Experimental results demonstrate the effectiveness of the Butterworth filter in enhancing images. The filter’s ability to selectively enhance desired frequency components while preserving important image details leads to improved image quality and visual perception. The evaluation metrics consistently show significant improvements in terms of image quality, contrast enhancement, and preservation of image details. The outcomes of this research aid in the comprehension of the Butterworth filter's capabilities and its potential applications in image enhancement tasks. The proposed method can be applied in various domains, including medical imaging, remote sensing, and computer vision, to improve image quality, facilitate analysis, and aid in decision-making processes.