TY - JOUR ID - 88439 TI - Digital Image Blurring Reduction using Modified Total Variation-based Guided Filter JO - Journal of Machine Vision and Image Processing JA - JMVIP LA - en SN - AU - Rahimi, Asma AU - Shayegan, Mohammad Amin AD - Ms. Student of Computer Engineering , Azad University, Shiraz Branch, Shiraz, Iran AD - Department of Computer, Faculty of Engineering, Azad University, Shiraz Branch, Shiraz, Iran Y1 - 2020 PY - 2020 VL - 7 IS - 1 SP - 1 EP - 16 KW - image enhancement KW - Image Sharpening KW - Image Blurring KW - Guided Filter DO - N2 - Nowadays, a huge amount of images are produced by digital cameras. However, various reasons such as weakness in the design of the camera lens, lead to the creation of noisy images.The image enhancement methods sharp some componentsof images such as the edges in order to increase the resolution of the input images.But, sharpening of the images' edges results in increasing the noise. Hence, in order to reduce the blurriness of images, employing of sharpening techniques should be applied under controlled conditions in order to prevent loosing images details. In this paper, a new method is proposed to reduce the blurriness of digital images. The proposed method is combination of Relative Total Variation filter (RTVf) and Rolling Guidance filter (RGf) in HSV color space. In the proposed method, the image structure is extracted by using RTVfand then the images' edges are retrieved by using RGf. Then, the image details are extracted by subtracting the V channel of input image from the result image of RGf. During a repetition process, image's details are added to image V channel.  In this method, the intensity of the image pixels does not change to a similar ratio, which results in better display of the image details and prevents increasing noises.The proposed method has been tested on benchmark images.The achieved results show that the proposed method achieved to 47% of reducing blurriness, 85% of noise controlling, and 83% of saving naturalness of input images in compared to rival methods. UR - https://jmvip.sinaweb.net/article_88439.html L1 - https://jmvip.sinaweb.net/article_88439_ba1c4f1322068eeefa19366b72f39f2e.pdf ER -