Three methods that improve the visual quality of colour anaglyphs

Transcription

1 Three methods that improve the visual quality of colour anaglyphs Journal of Optics A:Pure And Applied Optics, Vol. 7, No. 12, 2009 Inair Ideses, Leonid Yaroslavsky Presented by Woo-Heon Jang School of Electrical Engineering and Computer Science Kyungpook National Univ.

2 Abstract Anaglyphs Economical methods for three-dimensional visualization Severe drawback Loss of colour Extreme discomfort for prolonged viewing Proposed methods Anaglyph enhancement Reducing ghost artifacts Improvement of visual quality of images 2 / 24

3 Introduction Anaglyphs Artificial colour images Visual effect of 3D images using colour-filtering spectacles Two images as stereo pair Greyscale stereo images» Red channel from left image» Blue channel from right image 3D perception in images of unbalanced colour histogram Red hue» Unrelated hue to detail for 3D perception 3 / 24

4 Fig.1. The left image is an anaglyph created by transforming the stereo pair to greyscale and using the left image as the red component and the right image as blue component of the anaglyph. Suggesting method Enhanced image quality Retaining colour information Reducing ghost image appearance 4 / 24

5 Redundancy of stereoscopic images Stereoscopic images Two images of same scene Stereo pair Added second image by depth map in single image Depth map Number of depth gradation Determination by same order magnitude» Number of resolved image grey levels Determined signal volume by depth map samples 5 / 24

6 Image fragments Reliable localization on image Number of independent samples of depth map» Several times lower than number of image pixels» Several times lower than signal volume of image Decimation for division of stereo pair Interpolation for restoration of stereo pair Experiment Decimation and subsequent interpolation of stereoscopic image Performing stereo image for image quality 6 / 24

7 Fig. 2. Root-mean-squared error of parallax measurements as a function of the decimation factor as measured on 31 randomly selected fragments. Fig. 4. The left anaglyph was formed from two images of full resolution. The right anaglyph was formed from images of full resolution and of 1/5th of full resolution. Use the red filter for the left eye and the blue filter for the right eye. 7 / 24

8 Fig. 3. Full-resolution stereo pair (upper row) and stereo pair built from one image of full resolution and second image of 1/5th of full resolution (bottom row). 8 / 24

9 Anaglyph enhancement Low quality of anaglyph Ghosting artifact Misalignment of colour components Reducing artifact by acquiring images with low parallax Low 3D perception Three methods for reducing ghost artifact Stereo pair registration Colour component blurring Depth map manipulation and artificial stereo pair synthesis 9 / 24

10 Stereo pair registration Reduction of undesired ghost effect mean of registration of foreground Entire image Locally selected important object in image Global registration Efficient performance using correlation filter ( xˆˆ, y) = arg max( I I)( xy, ) arg max( I I)( xy, ) (1) where I 1 is one image of stereo pair, I 2 is second image, and symbolizes correlation in image coordinates ( xy, ). Image correlation Computation in discrete Fourier transform» Utilizing fast Fourier transform Multiplicatio by complex conjugate spectrum of second image 10 / 24

11 Cased of false registration Overall image correlation with few cases of fales registration Image fragment of small size Failure of conventional correlation technique Improving performance using adaptive correlator H( f, f ) = x y * α ( f, f ) 2 x β ( f, f ) W( f, f ) x y x y y (2) where α * ( fx, fy) β ( fx, fy) W( f, f ) x y 2 is complex conjugate spectrum of fragment of one image is squared module of DFT spectrum of second image, and is a spectrum smoothing window. 11 / 24

12 Fig. 5. Standard colour anaglyph without image registration (top image) and anaglyph enhanced by means of image registration (bottom image). Note the reduced ghosting artefacts in the enhanced anaglyph. 12 / 24

13 Defocusing anaglyph colour components Existence of residual artifact after alignment Representing 3D scene by large deviation of depth in object Visual fatigue Convergence Perceived distance» Estimation from stereo pair Accommodation Perceived distance of object by focusing of eye lens Perceived distance Different and correspond to 3D depth within image Causing discomfort» Viewed image for prolonged duration of time 13 / 24

14 Occurring conflict of cues Image in sharp focus Perceived depth from focal range in human visual system Smoothing image Alleviated problem of conflicting depth cue Color component blurring» Convolution in spatial domain with window of constant weight Nx y 1 Ixy (, ) = Ix ( nx, y ny) (2N + 1)(2N 1) = = x x N n N n N x x y y (3) where Ixy (, ) Ixy (, ) is blurred image, and is image before convolution. 14 / 24

15 Proper selection of colour components Conclusion for obtaining quality anaglyphs Blurring of red colour channel» Most useful method Blurring of green colour channel» Destruction of visual quality and 3D percetion» Higher sensitivity of human visual system Fig. 6. Defocusing anaglyph colour components. Anaglyphs in the left column were defocused in the red component, those in the middle in the green component, and right column anaglyphs underwent blue component defocusing. 15 / 24

16 Fig. 7. Defocusing anaglyph colour components. The original anaglyph (top image) has undergone defocusing of the red colour component (bottom image). Note the increased visual quality. (The top image was taken from NASA web site. 16 / 24

17 Improving anaglyphs by depth map manipulation Ghosting artifact Direct result of varying depth field in image Removing artifact by constant depth Increment of dynamic range of depth Reduction of unwanted effect Method for anaglyph improvement by depth map Depth map calculation from two stereo images Depth map dynamic range compression Stereo pair resynthesis with modified depth map and anaglyph creation 17 / 24

18 Depth map calculation Depth map manipulation Reducing dynamic range of depth map values» Compression of signal dynamic range by P-th law transformation P hxy (, ) = ah( xy, ) where hxy (, ) hxy (, ) P 0 1 Stereo pair resynthesis Generating stereo pair» image and modified depth map» Bilinear interpolation a is modified depth map sample value, is original depth map value, is < P <, and is a normalizing constant. (4) 18 / 24

19 Fig. 8. Stereo images (left and right images) and corresponding depth map (centre image). Although the resulting depth map does not show the exact metrics of the stereo pair, it is sufficient for the purpose of visualization. Fig. 9. Colour anaglyph of full depth map dynamic range (left) and that with P-law (P = 0.5) compressed depth map (right). Use the red filter for the left eye and the blue filter for the right eye. 19 / 24

20 Anaglyph viewing modes Evaluation of anaglyph Quality of colour anaglyph image Parameters of blur Depth map dynamic range compression View without colour spectacles View using colour scpetacles 20 / 24

21 Fig. 10. Observing a colour stereo image using one full colour and full resolution image (left) and one blurred image of very low colour saturation (right). 21 / 24

22 Table 1. Quantitative evaluation of enhancement methods. Note that for all images, enhanced anaglyphs have better viewing success percentages than their standard anaglyphs counterpart (for the same constructing stereo pair). Note also superior subjective quality marks. Quality marks are graded from 1 to / 24

23 Conclusions Anaglyphs Simple and economical methods for 3D visualization Proposed method Anaglyph enhancement by overcoming drawbacks Image alignment Blurring image colour component Compressing depth map dynamic range Improved result of anaglyph as high quality 23 / 24