A problem of fundamental importance in image processing is edge detection since an edge characterizes the boundaries. Edge detection filters out useless data, noise and frequencies while preserving the important structural properties in an image for further analysis and implementation. Due to limitations of the existing techniques finding a better method for edge detection is still an active area of research. . In order to augment the high-frequency components of an image in this paper we propose a new class of filter by name 'PSS filter' which implies a spatial filter shape with a high positive component at the centre. It is found that sharpening with PSS filter high lights some of the fine details of an image and enhances the clarity of its boundaries. Since the perception of human of image quality is not adequate some image quality metrics like Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Average Difference (AD), Normalized Absolute Error (NAE), Structural Content (SC), Normalized Cross Correlation (NCC) and Maximum Difference (MD) were employed for measurement of image quality. Experimental results show that the proposed PSS filter displayed better performance and superior noise resilience.

Image processing spatial filter image sharpening image smoothing PSS filter image quality metrics