Deconvolution is a mathematical process used in signal processing and image analysis to reverse the effects of convolution. Convolution is a common operation used to process signals or images by combining them with a filter or a kernel. Deconvolution aims to recover the original signal or image from the convolved data by estimating and removing the effects of the kernel. Deconvolution methods are used in various fields such as astronomy, microscopy, and medical imaging to enhance the resolution and quality of images. By deconvolving the images, researchers can remove blurring or artifacts caused by the imaging system and obtain clearer and more accurate representations of the underlying data. Deconvolution techniques vary in complexity and performance, and the choice of method depends on the specific application and requirements of the research project.