Noise is the information damage that may occur in the image due to the changes in information during the transmission process. In order to overcome these problems, it is necessary to do filtering process on the image. Until now many filtering algorithms have been proposed to remove noise. Most existing methods only work for low level noise. In this study, the authors proposed an efficient and easy‐to‐understand filtering algorithm using the concept of tropical algebra and singular value decomposition (SVD). The SVD will be used to detect noise in 3 × 3 templates. Furthermore, if noise is detected then new pixels will be obtained by using the concept of tropical operations. The results of this study show that the proposed method provides better results from the existing methods in terms of quantitative and visual.

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An image through the digitization process is referred to as a digital image. The quality of the digital image may be degenerating due to interferences on the acquisition, transmission, extraction, etc. This attracted the attention of many researchers to study the causes of damage to the information in the image. In addition to finding cause of image damage, the researchers also looking for ways to overcome this problem. There are many filtering techniques that have been introduced to deal the damage to the information in the image. In addition to eliminating noise from the image, filtering techniques also aims to maintain the originality of the features in the image. Among the many research papers on image filtering there is a lack of review papers which are an important to facilitate researchers in understanding the differences in each filtering technique. Additionally, it helps researchers determine the direction of research conducted based on the results of previous research. Therefore, this paper presents a review of several filtering techniques that have been developed so far.