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Health care, forgery and engineering are just a few of the many industries that rely on the content of images. Mobile phone cameras use image sensors with Bayer patterning. It is necessary to use a demosaicing algorithm to extract the fullcolour image with requisite quality. Content-based adaptive demosaicing utilising random forest algorithm is proposed in this article, as it has the advantage of being easy to train and evaluate. Interaction curvature was used as the predictor. Interpolation techniques: linear, closest, cubic, rational v4 precede this section. For each pixel, 50 learning cycles are utilised, and all of this work is done using MATLAB software. Using random forest algorithms, ten pictures are used to calculate PSNR, SNR, SSIM, and MSSIM. All of the test photos were more efficient when using Random forest as a filter.
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How to Cite
Walia G, Sidhu J. Content based Adaptive Image Demosaicing using Random Forest Algorithm. sms [Internet]. 30Jun.2022 [cited 29Nov.2023];14(02):183-6. Available from: https://smsjournals.com/index.php/SAMRIDDHI/article/view/2725
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