Adaptive lifting scheme with sparse criteria for image coding

Kaaniche, Mounir; Pesquet-Popescu, Béatrice; Benazza-Benyahia, Amel; Pesquet, Jean-Christophe

doi:10.1186/1687-6180-2012-10

EURASIP Journal on Advances in Signal Processing

Table 1 Performance of the proposed method vs the 9/7 transform

From: Adaptive lifting scheme with sparse criteria for image coding

		0.05 bpp		0.1 bpp		0.15 bpp		0.2 bpp
		NSLS(2,2)-OPT-WL1	9/7	NSLS (2,2)-OPT-WL1	9/7	NSLS (2,2)-OPT-WL1	9/7	NSLS (2,2)-OPT-WL1	9/7
	PSNR	27.85	27.75	30.25	30.31	31.23	31.35	31.76	31.92
elaine	SSIM	0.669	0.659	0.716	0.715	0.739	0.739	0.754	0.756
	VSNR	18.44	18.09	23.10	23.05	25.60	25.50	27.28	27.42
	PSNR	25.10	25.09	27.08	27.18	28.36	28.51	29.51	29.58
castle	SSIM	0.725	0.712	0.790	0.780	0.825	0.821	0.855	0.851
	VSNR	17.54	17.22	21.55	21.10	23.74	23.40	25.80	25.32
	PSNR	27.51	27.58	29.12	29.24	29.92	30.12	30.50	30.70
einst	SSIM	0.603	0.601	0.654	0.655	0.687	0.689	0.710	0.715
	VSNR	15.33	15.25	18.62	18.71	20.37	20.47	21.59	21.94
	PSNR	26.70	26.68	29.59	29.56	31.25	31.47	32.70	32.90
lena	SSIM	0.747	0.734	0.818	0.808	0.851	0.850	0.871	0.873
	VSNR	15.94	15.73	20.56	20.18	24.06	23.95	26.12	26.15
	PSNR	26.51	26.43	29.81	30.33	31.84	32.63	33.61	34.44
cameraman	SSIM	0.783	0.774	0.847	0.842	0.887	0.892	0.914	0.915
	VSNR	16.74	16.34	21.73	21.66	24.94	25.70	27.75	28.34
	PSNR	24.65	24.55	26.82	26.86	28.43	28.54	29.52	29.74
boat	SSIM	0.675	0.661	0.753	0.746	0.806	0.802	0.837	0.836
	VSNR	13.41	13.03	17.14	16.89	20.24	19.76	22.19	21.89
	PSNR	25.75	25.50	29.24	29.17	30.88	31.16	31.12	32.38
peppers	SSIM	0.720	0.705	0.789	0.778	0.818	0.815	0.834	0.832
	VSNR	16.00	15.51	21.87	21.19	25.18	25.00	27.22	27.09
	PSNR	24.19	23.84	30.66	29.88	33.99	33.10	36.13	35.82
plane	SSIM	0.809	0.754	0.890	0.871	0.917	0.903	0.931	0.921
	VSNR	9.48	7.72	17.73	15.51	21.28	20.30	24.68	24.12
	PSNR	24.88	24.72	27.67	27.73	29.24	29.46	30.45	30.65
average	SSIM	0.647	0.633	0.727	0.720	0.773	0.771	0.803	0.802
	VSNR	14.50	13.98	18.90	18.62	21.77	21.71	23.90	23.85

The average evaluation was computed over 50 still images.
The values in bold have been used to identify the method achieving the best coding performance.

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