In this work, a different Fourier single-pixel imaging technique that uses an intensity correlation algorithm to reconstruct images from obtained Fourier positive–negative imagesis used. The research is based on Fourier positivenegative intensity correlation for single pixel image processing.In single-pixel imaging, a set of mask patterns is employed to filter the scene. Single pixel imaging is a type of imaging that uses only one detector device.The goal of this study is to use the concept of positive – negative intensity correlation to obtain a clear image.Using intensity correlation, the negative and positive pictures are used to recreate a picture. To carry out the simulation, a Fourier matrix is created and divided into two parts: real cosine and imaginary sine.After obtaining discrete sampling points we reshaped these points to form a 2D square pattern. The pattern so obtained finally overlayed on the target image. The size of target image is selected on basis of Fourier matrix. Positive and negative images are obtained by overlaying the pattern on target image. The simulation is carried out using Python programming. We use the overlaying technique to combine positive and negative images to create a clearer image.An endless superposition of sine waves of varying frequencies can be characterised as any continuous signal. This theory is applied to a two-dimensional space, and a technique for imaging is proposed.Theexecuted simulations resulted in production of high-quality photographs, proving the technologies' viability.

Single pixel imaging; Positive-negative intensity correlation; Fourier matrix; overlaying