摘要：To overcome the shortcomings of traditional total variation (TV) denoising algorithm that is sensitive to noise and easy to blur, we propose an algorithm of image block denoising based on adaptive total variation for the cell image denoising. This algorithm uses image block method to segment cell image into flat region and edged region, then adaptively select the isotropic 2-norm total variation image denoising model for flat region or the anisotropic 1-norm one for edged region according to the local gray mean grads. To solve the border processing problem of blocked image, we just copy the neighboring pixels to fill the image border. Experimental results showed that, when adding Gaussian noise of 0 mean and variance of 0.01 to the blurred image, the method of image block denoising based on adaptive total variation can increase the Peak Signal-to-noise Ratio (PSNR) of the noise image by 10.72dB. Compared with the traditional denoising algorithms, our algorithm can not only preserve more texture details of the edge region, but also efficiently suppress the noise of the flat region, making it more suitable for biomedical cell image denoising
