Fish farmers are facing a huge loss in terms of productivity and economically due to emerging diseases in fish species. For the health monitoring and control of these diseases, it is essential to highlight the potential detection tools for fish. But it required a very fast, potent, and reliable strategy that possesses high automation and capabilities. To meet the requirements of the recent era, revolutionary technologies such as image processing have been introduced. This technology is extensively employed in disease detection, particularly in fish, human, and plant-related disease issues. Its result ensures high accuracy and treatment aiding potential for human experts to treat respective diseases. The particular mechanism of image detection includes various steps such as image acquisition, processing, segmentation, object detection, extraction of features, and organization. The main theme of this review is to emphasize the previously published literature regarding techniques related to image processing, including machine learning, rule-based expert systems, statistical, and hybrid methods. It is a matter of urgent concern which recent improvement in image processing should be explored, and fish farmers can enhance their performance through advancement in these techniques.