Optical visualisation techniques such as shadowgraph and Schlieren are commonly employed to study shockwave characteristics in supersonic free jets, to conduct qualitative as well as quantitative analysis. Typically, high-speed cameras are used to capture images with clearly visible shockwaves. The lower-cost cameras with lower frames per second (fps) do not yield satisfactory results. Therefore, there is a need to develop an algorithm capable of reducing image noise and enhancing the images from a low fps camera to enable better observation of shockwaves. In this study, a supersonic free jet exiting a CD nozzle with design Mach number 1.6 was visualised using the Schlieren method. Images were captured using a camera operating at 7 fps and processed using a MATLAB algorithm to reduce noise and bring out well-defined shockwave structures. The algorithm employed these series of steps: time averaging of images with shockwaves and images of the background, conversion of images to grayscale, application of a frequency-domain filter, and subtraction of the background image from the supersonic jet image. Qualitative analysis was performed on the processed images that revealed prominent features such as the shock cells, vortices generated by chevrons, and the Mach disc in highly overexpanded jets. Quantitative analysis was also done to measure shock angle and Mach stem length. Additionally, image processing brought out the previously unseen shear layer in the original images. This algorithm holds potential for cost reduction in optical visualisation experiments by eliminating the requirement for a high fps camera to achieve reliable qualitative analysis.