Wavelet HSI / [1] JPEG2000 9/7Wavelet [2][6] 2:1 9/7Wavelet Wavelet 80 Wavelet i
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1 17 Wavelet Image Enhancement by Wavelet Transform
2 Wavelet HSI / [1] JPEG2000 9/7Wavelet [2][6] 2:1 9/7Wavelet Wavelet 80 Wavelet i
3 Abstract Image Enhancement by Wavelet Transform Yuichi Taoka The amount of operations in the highpass and lowpass filters is too large to process our color image enhancement algorithm in real-time which uses HSI local luminance and contrast signals. Therefore, a simplified method is introduced which replaces filters with the 9/7Lifting Wavelet transform, used in JPEG2000. In this method, the amount of operation can be reduced by processing 2:1 down sampling at the input port. However in this method, a clear distortion appears around the edge of the output image. The reason seems to be the frequency characteristics of 9/7Lifting Wavelet transform filter, where an overlap characteristics at the cut-off frequency is quite wide. Therefore, overlapped spectrum is no more cancelled in the synthesis phase, if either high or low frequency area is enhanced. In order to suppress such distortion, a novel adaptive edge enhancement algorithm is proposed. By this method, only weak hidden signals are enhanced without generating distortion around clear edges. As a result, the subjectivity evaluation of the proposed method shows good characteristic in picture enhancement. This method reduce one-order less the amount of operation. key words Image Enhancement, Wavelet Transform, Lifting stracture ii
4 ( Wavelet ) HSI HSI (1) (2) (3) Wavelet Wavelet Wavelet Wavelet Wavelet Wavelet iii
5 iv
6 2.1 HSI I S HSI n = n = /7Wavelet Wavelet v
7 4.1 Wavelet Wavelet /7Wavelet tapQMF tapQMF ( 1) ( 2) Wavelet HSI vi
8 (n ) (n ) vii
9 1 1.1 PDA [3][4] HSI / [1] Wavelet JPEG2000 9/7Wavelet [2] 9/7Wavelet 1 1
10 Wavelet HSI Wavelet 9/7 Wavelet HSI 80 HSI 2
11 2 ( Wavelet ) 2.1 HSI [7] 3 Wavelet 9/7Wavelet HSI HSI [5] H S I 2.1 HSI RGB ( 2.1 ) CMY ( 2.1 ) HSI ( 2.1 ) RGB HSI I = max(r, G, B) (2.1) 3
12 I = 0 S H S = 0 H = (2.2) 2. I 0 S S = r, g, b I min(r, G, B) I (2.3) I R r = I min(r, G, B) I G g = I min(r, G, B) I B b = I min(r, G, B) (2.4) H R = I H = π (b g) 3 G = I H = π (2 + r b) 3 B = I H = π (4 + g r) (2.5) 3 HSI RGB R G B 1/3 2.2 I 2.2(a) P I I I 1 I 1 P S S 2.2(b) I V V 4
13 2.1 C I G B Y M R H S 印 :RGB 表色系 印 :YCM 表色系 印 :HSI 表色系 2.1 HSI 2.2 I S HSI (1) 2.3 HSI H S I 5
14 HSI + - f H f ' f H f コントラスト強調関数 f ' 低域通過フィルタ f L 局所明度調整関数 f L' L ' 2.4 I I H S HSI I 2.4 f 2 f L f L f f L f H f H f L f L f H f H f L f H f 6
15 2.1 グループ 1 グループ (2) [1] (2.6) y = a + αx n (n = 0.5, 1) (2.6) x y n 1 2 a, α 2.6 n = n = 1.0 ( 2.5 2) n = 0.5 ( 2.5 1) n = 1.0 7
16 n = n = 1.0 コントラスト成分 細部信号のヒストグラム抽出 ヒストグラム平滑化 重み付け コントラスト強調関数 局所明度成分 2.8 (3) 2.8 f L f H 1 3 8
17 HSI [8]
18 2.1 カラー画像強調 図 2.9 夜の交差点 原画像 図 2.10 霧 原画像 10
19 2.1 カラー画像強調 図 2.11 夜の交差点 画像強調後 図 2.12 霧 画像強調後 11
20 2.2 Wavelet 2.2 Wavelet 3 Wavelet Wavelet Wavelet Wavelet H 0 (z) G 0 (z) H 1 (z) G 1 (z) 2 2:1 2 1: Wavelet Wavelet X (z) H ( z 0 ) H 1 ( z) G 0 ( z) G 1 ( z) + - X (z) 分析 合成
21 2.2 Wavelet H 0 ( z) 2 LL H ( z 0 ) 2 X (z) H ( z 1 ) 2 LH H 1 ( z) 2 垂直方向の分析 H ( z 0 ) H 1 ( z) 水平方向の分析 2 2 HL HH Wavelet LL LH HL HH LL 2:1 2:1 LH 2:1 2:1 HL 2:1 2:1 HH 2:1 2:1 13
22 2.2 Wavelet 3LL 3HL 3LH 3HH 2LH 1LH 2HL 2HH 1HL 1HH LL Mallart Wavelet Wavelet Wavelet Wavelet Wavelet Wavelet Wavelet Wavelet 2: /7 14
23 2.2 Wavelet /7Wavelet Wavelet 9/7 Wavelet 9/7 6 (1) (4) 1 (5) (6) X Y Wavelet (1) n Y (2n + 1) = X(2n + 1) + α[x(2n) + X(2n + 2)] (2.7) (2) n 1 Y (2n) = X(2n) + β[y (2n 1) + Y (2n + 1)] (2.8) (3) n 1 2 Y (2n + 1) = Y (2n + 1) + γ[y (2n) + Y (2n + 2)] (2.9) (4) n 2 3 Y (2n) = Y (2n) + δ[y (2n 1) + Y (2n + 1)] (2.10) (5) n 3 6 Y (2n + 1) = KY (2n + 1) (2.11) 15
24 2.2 Wavelet (6) n 4 Y (2n) = Y (2n)/K (2.12) α β γ δ K
25 3 Wavelet 3.1 PDA 2 2 Wavelet Wavelet 2 Wavelet Wavelet (3.1) 17
26 3.3 Wavelet 2 加算 : n 2 乗算 : n f ' + - f H f H f コントラスト強調関数 2 加算 : n f ' 2 加算 : n 低域通過フィルタ 加算 : 乗算 : 81n 81n 2 2 f L 局所明度調整関数 加算 : 乗算 : n 10n 2 2 f L' L ' n X(n 2 ) = 163n n 2 (n ) (3.1) (3.1) 2 2 Wavelet 3.3 Wavelet Wavelet Wavelet 1 4 Wavelet 18
27 (n ) (n 2 ) Wavelet 3.2 Wavelet f Wavelet LL LH HL HH 4 LL LH HL HH LL LH HL HH Wavelet f 3.3 Wavelet LL LH HL HH LL LH HL HH LL HSI Wavelet Wavelet C 19
28 Wavelet LL 局所明度成分の画像強調 LL LH コントラスト成分の画像強調 LH HL コントラスト成分の画像強調 HL HH コントラスト成分の画像強調 HH Wavelet Wavelet 20
29 /7Wavelet 21
30 4 4.1 Wavelet Wavelet
31 4.2 2 f s f s 0 f s 2 fs Highpass Filter Lowpass Filter (a) Signal Subband Filter (b) Lowpass Filtered Signal (c) Highpass Filtered Signal (d) Lowpass Filtered Signal (e) Highpass Filtered Signal 2:1 Down Sample (f) Lowpass Filtered Signal (g) Highpass Filtered Signal (a) (b) (c) (d) (e) (f) (d) (g) (e) 4.1 Wavelet Wavelet 4.1 Wavelet Wavelet Wavelet fig:wavelet (a) (b) (c) (d) (e) fs 2 (d) (e) 23
32 4.2 2 f s f s 0 f s 2 fs (a) Lowpass Filtered Signal (b) Highpass Filtered Signal 1:2 Up Sample (c) Lowpass Filtered Signal (d) Highpass Filtered Signal Subband Filter (e) Lowpass Filtered Signal (f) Highpass Filtered Signal (g) Lowpass Filtered Signal (h) Highpass Filtered Signal Lowpass - Highpass (i) Signal (a) (b) (c) (a) (d) (b) (e) (c) (f) (d) (g) (h) (i) 4.2 Wavelet Wavelet 2:1 (d) (e) (f) (g) (f) (g) Wavelet 4.2 Wavelet
33 /7Wavelet (a) (b) 1:2 (c) (d) (e) (f) (e) (f) (g) (h) (g) (h) (i) Wavelet 4.1 (f)(g) Wavelet Wavelet 9/7Wavelet /7Wavelet 25
34 highpass jω 1 ) e ( H 0.5 lowpass Frequency ω [rad] tapQMF 4.3 Wavelet Wavelet 9/7Wavelet 9/7Wavelet 16tapQMF 32tap QMF 16tapQMF tapQMF
35 highpass jω 1 ) e ( H 0.5 lowpass Frequency ω [rad] tapQMF /7Wavelet (LH,HL,HH) 25 27
36 Wavelet 4.14 Wavelet 28
37 ( 1) 4.10 ( 2)
38 Wavelet
39 5 5.1 Wavelet ITU-BT
40 (n ) (n 2 ) 被験者 5H H H ( 1,2 ) 2 3 MOS
41 値 S O 3.5 M 提案法局所明度のみ強調 画像 1 画像 2 画像 3 画像 4 画像 5 評価画像 HSI ( 5.5) HSI π π 1 2π π Wavelet LL Wavelet 33
42 5.4 従来方法と提案法の比較 図 5.3 原画像 図 5.5 提案法 図 5.4 HSI 局所明度コントラスト方式 周波数特性を 14 π π にできる このアプローチと高周波成分の LH HL HH の画一的で はない強調に関して今後の検討課題である 34
43 6 Wavelet Wavelet 2:1 Wavelet Wavelet 80 Wavelet LH HL HH Wavelet 1 35
44 4 3 36
45 [1] Y.Taoka K.Takakashi T.Sato T.Nishitani Consideration on Adaptive Image Enhancement,, [2] Ingrid Daubechies Wim Sweldens Factoring Wavelet Transforms into Lifting Steps,, J.Fourier Anal.l Appli, vol.4, No.3, pp , [3] 2,, [4] Ichiro KURODA Adaptive Image Enhancement Algorithms and Their Implementation for Real-Time Video Signals, IEICE TRANS. FUNDAMENTALS, VOL.E84-A, NO.2 FEBRUARY 2001 [5],, pp , 2004 [6] JPEG2000,, pp , 2003 [7] Kotaro Takahashi, Yuichi Taoka, Toshihiro Sato and Takao Nishitani, Picture Quality Enhancment with Color and its Evaluation, NEINE 2005 [8],,
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