Super resolution reconstruction for medical image based on adaptive multi-dictionary learning and structural self-similarity

Figures & data

Figure 1. The image pyramid generated by self-similarity.

Figure 2. The algorithm flow chart of this paper.

Figure 3. Comparison of the reconstructed images of various methods for noiseless medical image (1(1) $$x\approx \Phi \alpha$$(1) ) (a) Original image (b) LR image (c) Bicubic (d) ASDS (e) Our.

Figure 4. Comparison of the reconstructed images of various methods for noiseless medical image (2(2) $$\alpha =\underset{\alpha }{\arg \min }{\parallel \alpha \parallel }_0,s.t.{\parallel x-\Phi \alpha \parallel }_2\le \epsilon$$(2) ) (a) Original image (b) LR image (c) Bicubic (d) ASDS (e) Our.

Figure 5. Comparison of the reconstructed images of various methods for noiseless medical image (3(3) $$\alpha =\underset{\alpha }{\arg \min }{\parallel \alpha \parallel }_1,s.t.{\parallel x-\Phi \alpha \parallel }_2\le \epsilon$$(3) ) (a) Original image (b) LR image (c) Bicubic (d) ASDS (e) Our.

Figure 6. Comparison of the reconstructed images of various methods for noisy medical image (1(1) $$x\approx \Phi \alpha$$(1) ) (a) Original image (b) LR image (c) Bicubic (d) ASDS (e) Our.

Figure 7. Comparison of the reconstructed images of various methods for noisy medical image (2(2) $$\alpha =\underset{\alpha }{\arg \min }{\parallel \alpha \parallel }_0,s.t.{\parallel x-\Phi \alpha \parallel }_2\le \epsilon$$(2) ) (a) Original image (b) LR image (c) Bicubic (d) ASDS (e) Our.

Figure 8. Comparison of the reconstructed images of various methods for noisy medical image (3(3) $$\alpha =\underset{\alpha }{\arg \min }{\parallel \alpha \parallel }_1,s.t.{\parallel x-\Phi \alpha \parallel }_2\le \epsilon$$(3) ).

Table 1. Comparison of PSNR (dB)/SSIM of the medical images ($\sigma =0$) based on various methods.

Test Images	Bicubic	ASDS	Our
Head1	22.26	27.14	27.40
	0.7371	0.8906	0.8970
Head2	24.15	29.46	29.86
	0.8005	0.9136	0.9166
Chest	21.23	24.16	24.66
	0.4490	0.5597	0.5666

Table 2. Comparison of PSNR (dB)/SSIM of the medical images ($\sigma =5$) based on various methods.

Test Images	Bicubic	ASDS	Our
Head1	22.09	25.03	25.51
	0.5662	0.6310	0.6385
Head2	23.87	27.13	27.51
	0.6046	0.6288	0.6306
Chest	21.09	23.40	23.83
	0.3742	0.4254	0.4391

Table 3. Comparison of complexity.

Item	Bicubic	ASDS	Our
Complexity	$O\left(n^3\right)$	$O\left(n^3\right)$	$O\left(n\right)$
Time consumption	2.74s	3.84s	2.52s

Figure 9. Comparison of the reconstructed images of various methods for Butterfly image (a) Original image (b) Bicubic (c) Yang (d) Our.

Table 4. Comparison of PSNR (dB)/SSIM of the reconstructed images based on various method.

Test Images	Bicubic	Yang	Our
hat	28.27/0.8005	29.09/0.8263	31.44/0.8793
castle	25.61/0.7712	26.12/0.7935	26.98/0.8292
Input3	27.36/0.8892	28.51/0.9163	33.03/0.9643
average	27.08/0.8203	27.91/0.8454	30.48/0.8909