# Study on Image Filtering -- Techniques, Algorithm and Applications

arXiv: https://arxiv.org/abs/2207.06481 · HTML: https://mlsanity.com/paper/2207.06481/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 26 references that are in the map.
- First posted on arXiv 4 Jun 2022.

## Builds on (most cited first, 4 of 4)

- [Image-based Face Detection and Recognition: "State of the Art"](https://mlsanity.com/paper/1302.6379/) (2013)
- [Image Restoration in Non-Linear Filtering Domain using MDB approach](https://mlsanity.com/paper/2204.09296/) (2022)
- [Adaptive Non-linear Filtering Technique for Image Restoration](https://mlsanity.com/paper/2204.09302/) (2022)
- [Cyber-Forensic Review of Human Footprint and Gait for Personal Identification](https://mlsanity.com/paper/2204.09344/) (2022)

## Built on by (most cited first, 1 of 1)

- [Semi-Supervised Object Detection: A Survey on Progress from CNN to Transformer](https://mlsanity.com/paper/2407.08460/) (2024)

## Abstract (arXiv)

Image processing is one of the most immerging and widely growing techniques making it a lively research field. Image processing is converting an image to a digital format and then doing different operations on it, such as improving the image or extracting various valuable data. Image filtering is one of the fascinating applications of image processing. Image filtering is a technique for altering the size, shape, color, depth, smoothness, and other image properties. It alters the pixels of the image to transform it into the desired form using different types of graphical editing methods through graphic design and editing software. This paper introduces various image filtering techniques and their wide applications.