Visual prosthesis opens new perspectives in the field of restoring vision for blind people. It aims to bypass the defective stages of the natural visual pathway and to provide proper inputs to the later stages. The starting point of any visual prosthesis is an image processing model which is typically performed in two phases: Feature extraction to highlight the important information of visual scene, followed by a visual pathway stimulation which replaces the functionality of the defective stages of the visual pathway. This paper introduces a MATLAB toolbox for visual prostheses to handle all the required image processing. This toolbox supports the most common image processing techniques needed for both static and dynamic scenes recognition. In addition, it supports different kinds of visual prostheses like retinal and thalamic visual prostheses depending on how deep the visual stimulation phase will go. The paper demonstrates the value of the toolbox through a case study in which it was used for a simulated thalamic visual prosthesis.