Fig. 1. (a) CLI image of vivo experiment; (b) histogram of CLI image

Fig. 2. CLI images in numerical simulation. (a) Digital mouse, CL source location is the red point in blue circle; (b) simulated CLI image; (c) simulated CLI image after adding noises

Fig. 3. Denoising results of median filter algorithm with sliding window sizes of (a) 3, (b) 5, and (c) 7, as well as (d) denoising result of FLICMTV algorithm

Fig. 4. RMSE and SSIM of median filter and FLICMTV denoising algorithms. (a) RMSE of ROI; (b) SSIM of ROI; (c) RMSE; (b) SSIM

Fig. 5. Results of physical phantom experiment. (a) Original CLI image; (b) denoised CLI image with FLICMTV algorithm; (c) denoised CLI image with median filter algorithm with sliding window size of 5; (d) pixel intensity at red lines; (e) SSIM of different denoising algorithms in yellow rectangle

Fig. 6. Results of in vivo experiment. (a) White-light image of mouse, pseudotumor area is outlined in red circle; (b) original CLI image; (c) denoised CLI image with FLICMTV algorithm; (d) denoised CLI image with median filter algorithm with sliding window size of 5; (e) RMSE and (f) SSIM (red circle and all picture) for median filter and FLICMTV algorithms; (g) mean pixel intensity of ROI in fig. 6 (b), (c), and (d), respectively

Table 1. FLICMTV denosing algorithm