YUV is used in the European television system a color coding method (of PAL), the PAL and SECAM analog color television system used in the color space. In modern color television systems, commonly used three-color CCD camera or color camera for taking images, and then the color image signal obtained by the separation, respectively, after correction has been enlarged RGB, and then get through the matrix conversion circuit luminance signal Y and two a color difference signals R-Y (that is, U), B-Y (ie V), finally sending the brightness and color difference signals are encoded using the same channel to send out. This color representation is called the YUV color space representation. The importance of using YUV color space is its luminance signal Y and chrominance signals U, V are separate.
July 13, 2007 (Class 4: 1/2007) ENE 461 Introduction to Digital Image Processing Werapon Chiracharit, Ph.D., ENE, KMUTT YUV (YCbCr) Color Model Y=R+G+B U=B-Y V=R-Y Y is the lumimance (brightness) U is the chrominance blue-luma difference V is the chrominance red-luma difference 1 Otsu’s Thresholding • Probability distribution from histogram, Pi=ni/N • For any threshold = k for bimodal assumption • Frequency, ω1=Σ0→kPi and ω2=Σk+1→L-1Pi • Mean, µ1=Σ0→kiPi/ω1 and µ2=Σk+1→L-1iPi/ω2 Mean total, µt=ω1µ1+ω2µ2 • Variance between classes, δ2b=ω1ω2(µ1- µ1)2 • Variance total, δ2t= Σ0→L-1(i- µt)2Pi • Criterion function, η=δ2b/ δ2t • Choose threshold k that MAX η Line – 1st Order Polynomial The line from 2 points (x1,y1) and (x2,y2) Ax + By + C = 0 Known x1, y1, x2, y2 Unknown A, B, C Y y2 (x2,y2) y1 (x1,y1) 0 x1 x2 X 2 Pseudo-Inverse Matrix y = -(A/B)x – (C/B) y1 = -(A/B)x1 – (C/B) y2 = -(A/B)x2 – (C/B) y1 = -x1 -1 A/B y2 -x2 -1 C/B 2×1 2×2 2×1 -1 A/B = -x1 -1 y1 C/B -x2 -1 y2 2×1 2×2 2×1 Slope – 1st Derivative Number + - of Pixel + - 0 255 Intensity HISTOGRAM 3 Labeled Pixels For X = 1:Height For Y = 1:Weight I(X,Y) y-1 y y+1 Up Up x-1 Left Up Right (x-1,y-1) (x-1,y) (x-1,y+1) x Left Here Right 1 2 3 (x,y-1) (x,y) (x,y+1) Down Down 4 5 Left Down Right x+1 (x+1,y-1) (x+1,y) (x+1,y+1) 6 8 7 Cropping Y y1 y2 0 x1 x2 I(x1:x2,y1:y2) X 4 Scale-Down Interpolation I(x′) = λ I(x1) + (1- λ) I(x2) Intensity I(x1,y1) Intensity I(x2) 0 y 1 x1 I(x1) Pixel(x1,y1) Y X λ 1-λ 0 x1 x2 X Image Interpolation X,Y I(X,Y′) X,Y+1 X′,Y′ I(X′,Y′) X+1,Y I(X+1,Y′) X+1,Y+1 5 Scale-Up Interleave and Interpolation X,Y 0 X,Y+1 0 0 0 X+1,Y 0 X+1,Y+1 Rotation Y′ Y Y X X θ X′ 6 Rotated Axis X′ = cosθ -sinθ X Y′ sinθ cosθ Y Y X 0 Scaling 1.2y y 0.7y 1.2x 0.7x x 7 MATLAB Toolbox Functions • imrotate(I,θ-degree) => counter-clockwise • imresize(I,M-times) => M=[0,1] scale down => M>1 scale up imresize(I,[height,width]) => fixed size • zeroint(I) No Assignment ☺ When you hear, you forget. When you see, you remember. When you do, you Understand. 8 Exercise • By using no MATLAB scaling function, rotate your image (clockwise and anti-clockwise) • Resize your image (smaller scaling and enlargement) HAVE FUN ☺ 9
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