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1 Enhanced Film-Grain-Noise Removal Filter for High Fidelity Video Coding In this paper, we propose a novel technique for film grain noise removal, which can be adopted in high fidelity video coding in order to digitize analog films. Film grain noise enhances the natural appearance of high fidelity video, therefore it is should be preserved. However, film grain noise is a burden to typical video compression systems because it has relatively large energy level in the high frequency region. In order to improve the coding performance while preserving film grain noise, the noise removal and synthesis process is used. We propose a film grain noise removal technology in the pre-processing step. In pre-processing step, film grain noise is removed by using temporal and inter-color correlation. Specially, color image denoisng using inter color prediction provides good denoising performance in noise concentrated B plane because film grain noise has inter-color correlation in the RGB domain. The results show that the coding gain of denoised video is higher than for previous works, while the visual quality of the final reconstructed video is well preserved. Keywords: Film grain noise, Video denoising, Inter-color correlation, Bilateral filter, High fidelity video coding

3 II f t f t N(f t ) n w f t n t (1) f t n t t

4 N(f t ) f t n w n w f t f t M f t 1 f t 2... f t M p t m p t m p t m p p t m m 1,2,...,M r t m m 1,2,...,M f t p t m f t p t m f t w [w 0,w 1,...,w M ] T d ε E[(f t f t )2 ] ε w 0 ε d 0 w d Cov 1 (g t )1 w T (6) 1 T (g t )1 d w T t r t, (7) f t f t 1 r t n t, (2) f t [f t,p t 1,p t 2,...,p t M ]T 1 [1,1,...,1] T (M 1) r t [0,r t 1,r t 2,...,r t M ] T r t [n t,r p t 1,r p t 2,...,r p t M ]T r p t m m 1,2,...,M n t n t f t E(f t,n t ) E(f t N(f t ))E(n w ) 0 r t [0,r t 1,r t 1,...,r t M ] T Cov 1 (g t ) g t 1 E[n t,g t i ] E[n t (r t i n p t i )] 0, i 1,2,...,M n t g t i Cov (n t,g t i ) 0 i 1,2,...,M E[r t i,n p t j ] E[f t p t i )n p t j ] 0 g t i g t j Cov(g t ) Cov(g t ) diag(σ 2 n t,σ 2 n t 1,σ 2 n t 2,...,σ 2 n t M ) (8) E(p t m n t m ) 0,m 1,2,...,M, (3) w d f 1 t f t 1 g t, (4) σ 2 n 0 w0 M Σ σ 2 g t m σ 2 n t m 1 g t [ n t,g t 1,g t 2,...,g t M ] T g t m r t m n t m f t f t σ 2 g t m wm M Σ σ 2 g t m σ 2 n m 1 t f t w T f t d, (5) M d Σ w m r t m m 1 (9) n t n p t f t p t f t f t n t p t p t n p t g t m z t m f t p t m, m 1,2,...,M g t m r t m n p t m

5 z t m g t m n t n t n p t m r t m z t m z t m g t m n t σ 2 z t m σ 2 g t m σ 2 n 2E[g t t m n t ] σ g 2 t m σ 2 n t σ z 2 t m σ g 2 t m σ 2 n t σ z 2 t m e t f t f t M σ 2 e t Σ σ 2 r t m σ 2 n, (10) t m 1 f c n c c f c f c n c, c R,G and B, (11) n c N(f c ) n w n w f c p G R p G B p c k p c k n p c k f G f G w G R p G R w G f G w G B p G B d G, (12) w G R w G w G B p G R p G B

6 σ 2 n G w G σ 2 n G σ 2 n G B σ 2 n G R σ 2 n G w G c σ 2 n G σ 2 n G B σ 2 n G R d G w G B r wg R r, (13) G B G R D 1 D 1 D 1 DΣ {f k (i)f c (i)} { Σ f k (i)}{ Σ f c (i)} i 0 i 0 i 0 a k c, (16) D 1 D 1 D{ Σ f k (i)}2 { Σ f c (i)}2 i 0 i 0 r G c f G p G c σ 2 n G c r G c c p k c a k c f c b k c, (14) a k c b k c 1 D 1 D 1 b k c { Σ f k (i) a k c Σ f c D i 0 i 0 (i)}, (17) D f k f c E min E{(f k a k c f m b k c )2 }, (15) f k f c (f k f c ) (n k n c ), (18)

7 ρ nk n c f k f c σ 2 (f k f c ) σ 2 (f k f c ) σ 2 n k σ 2 n c 2 ρ nk n c σ nk σ nc, (19) f k f c E σ (f 2 k f c ) σ (f 2 k f c ) σ 2 (f k f c ) TH σ 2 n k σ 2 n c 2 ρ nk n c σ nk σ nc, (20) f t,c f t,c N(f t,c ) n w, (21) t t c f t,c t c f t 1,c f t 2,c... f t M,c f t,c 1 f t,c p t m,c p t,c k p t m,c p t,c k p t m,c p t,c k n p t m,c n p t,c k m 1,2,...,M k 1,2p t m,c p t,c k r t m,c f t,c p t m,c r t,c k f t,c p t,c k m 1,2,...,M k 1,2 f t,c p t m,c p t,c k f t,c f t,c f t,c 1 r t,c n t,c, (22) f t,c [f t,c, p t 1,c, p t 2,c,..., p t M,c, p t,c 1, p t,c 2 ]T 1 [1,1,...,1](M 3) r t,c [0,r t 1,c,r t 2,c,..., r t M,c, p t,c 1, p t,c 2 ] T n t,c [n t,c n p t 1,c,n p t 2,c,..., n p t M,c, n p t,c 1, n p t,c 2 ]T n p t m,c m 1,2,...,M n t,c f t,c f t,c 1 g t,c, (23) g t,c [ n t,c g t 1,c, g t 2,c,..., g t M,c, g t,c 1, g t,c 2 ] T g t m,c r t m,c r t m,c f t,c f t,c f t,c w T f t,c d, (24) w [w 0,w 1,...,w M,w M 1,w M 2 ] T d ε E[(f t,c f t,c )2 ] ε w 0 ε d 0 w d Cov 1 (g t,c )1 w T (25) 1 T (g t,c )1

8 d w T r t,c, (26) r t,c [0,r t 1,c,r t 2,c,..., r t M,c, r t,c 1, r t,c 2 ] T e t,c f t,c f t,c M 2 σ 2 e t,c Σ σ 2 r t m,c Σ σ 2 m 1 k 1 r t,c k σ 2 n t,c, (27) III

IV [1] N. Salvaggio, Basic photographic materials and processes 3rd edition, Focal Press, 2009. [2] C. Gomila and A. Kobilansky, "SEI message for film grain noise," Proc.

10 IV [1] N. Salvaggio, Basic photographic materials and processes 3rd edition, Focal Press, [2] C. Gomila and A. Kobilansky, "SEI message for film grain noise," Proc. 8th Meeting Joint Video Team, Doc. JVT-H022, Geneva, Switzerland, May 2003, pp [3] C. Gomila, "SEI message for film grain encoding: syntax and results," Proc. 9th Meeting Joint Video Team, Doc. JVT-I013r2, San Diego, California, USA, Sep. 2003, pp [4] "Film grain technology -Specifications for H.264 MPEG-4 AVC bit-streams," Society of Motion

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À±½Â¿í Ãâ·Â Representation, Encoding and Intermediate View Interpolation Methods for Multi-view Video Using Layered Depth Images The multi-view video is a collection of multiple videos, capturing the same scene at