Image de-noising algorithm based on image reconstruction and compression perception

Zhao, Baohui; Huang, Wenzhun; Wang, Haoxiang; Liu, Zhe

doi:10.1109/icici.2017.8365188

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Cited by 9 publications

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“…Research is running to upgrade the performance of the denoising algorithm [16], [17], [25], [26]. As mentioned before, researchers tried to get the best proficiency among the filtering techniques with various classes of images.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Image Denoising Technique for Unprocessed Raw Images using Combine Linear and Non-Linear Filtering

Rahman¹,

Anwar²,

Razaul³

et al. 2020

IJCA

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Image denoising is used to improve the accuracy and quality of an image. Removing noise from the original image is still challenging for researchers. In this research, an efficient algorithm capable of removing noise from "unprocessed" or raw images is proposed. The algorithm supplants the noise by the median of averages found from a special combination of the pixels. After that, to evaluate the performance of image authors has calculated the Signal to Noise Ratio (SNR), the Mean Square Error(MSE), Root Mean Square Error (RMSE), the Root Mean Square Signal to Noise Ratio (RMS SNR), Image Fidelity (IFY). Finally, the proposed filtering technique gives a better result with comparison to other existing filtering techniques (Median, Average, Mean, etc).

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Section: Introductionmentioning

confidence: 99%