Method and system for rendering simulated depth-of-field visual effect
Systems and methods for rendering depth-of-field visual effect on images with high computing efficiency and performance. A diffusion blurring process and a Fast Fourier Transform (FFT)-based convolution are combined to achieve high-fidelity depth-of-field visual effect with Bokeh spots in real-time applications. The brightest regions in the background of an original image are enhanced with Bokeh effect by virtue of FFT convolution with a convolution kernel. A diffusion solver can be used to blur the background of the original image. By blending the Bokeh spots with the image with gradually blurred background, a resultant image can present an enhanced depth-of-field visual effect. The FFT-based convolution can be computed with multi-threaded parallelism.
1. A computer implemented method of rendering an image, the method comprising:
accessing a first image represented in a space domain, said first image comprising a first section and a second section;
applying a blur operator on said second section to generate a second image;
identifying a plurality of target regions from said second section in said first image;
converting said plurality of target regions from said space domain to a frequency domain by performing a convolution thereon;
restoring said plurality of target regions in said first image from said frequency domain to said space domain to produce a third image; and
blending said second image and said third image to produce a resultant image.
2. The computer implemented method of claim 1 , wherein said converting and said performing a convolution comprises performing a Fast Fourier Transform (FFT) convolution on a convolution kernel with said plurality of target regions, and wherein said convolution kernel represents a hexagon camera aperture.
3. The computer implemented method of claim 2 , wherein a size of said convolution kernel corresponds to a circle of confusion (CoC) at an infinite distance.
4. The computer implemented method of claim 2 further comprising configuring a plurality of execution threads to perform said FFT convolution in parallel.
5. The computer implemented method of claim 1 , wherein said identifying said plurality of target regions comprises: down-sampling said first image to a downsized image;
filtering said downsized image with a bright pass filter based on a configurable luminance threshold.
6. The computer implemented method of claim 1 , wherein said first section corresponds to an in-focus subject represented in said first image, and wherein further said second section corresponds to a background represented in said first image.
7. The computer implemented method of claim 1 , wherein said blur operator comprises a diffusion depth-of-field solver, and wherein further said resultant image comprises Bokeh effect components.
8. A system comprising
a processor;
a memory coupled to said processor and storing an image processing program, said image processing program comprising instructions that cause said processor to perform a method of generating an image, said method comprising:
accessing a first image;
identify a first portion and a second portion of said first image;
selecting a plurality of regions from said second portion of said first image, said plurality of regions comprising luminous regions on said first image;
performing a Fast Fourier Transform (FFT) convolution on said plurality of regions with a convolution kernel representing a geometric shape to produce an intermediate image;
performing an inverse FFT convolution on said intermediate image to produce a second image;
applying a blur operator on said second portion of said first image and preserving said first portion to produce a third image; and
combining said second image and said third image to produce a resultant image.
9. The system of claim 8 , wherein said blur operator comprises a diffusion depth-of-field (DOF) solver, and wherein said resultant image presents a Bokeh effect.
10. The system of claim 8 , wherein said Fast Fourier Transform (FFT) convolution converts said plurality of regions from a space domain to a frequency domain, and wherein said convolution kernel represents a camera aperture shape with a size equal to a circle of confusion (CoC) at an infinite distance of said first image.
11. The system of claim 8 , wherein said selecting said plurality of regions comprises: down-sampling said second portion of said first image to a reduced-resolution image, and applying a bright pass filter on said reduced-resolution image based on a luminance threshold.
12. The system of claim 8 , wherein said method further comprises configuring a plurality of execution threads to perform said FFT convolution and said inverse FFT convolution respectively in parallel.
13. The system of claim 8 , wherein said first portion corresponds to an in-focus subject, and wherein said second portion corresponds to a background.
14. A non-transitory computer-readable storage medium comprising instructions, when executed by a processor, cause the processor to implement a method of generating an image, said method comprising:
accessing a first image;
identify a first portion and a second portion of said first image;
selecting a plurality of regions from said second portion of said first image, said plurality of regions comprising luminous regions on said first image;
performing a Fast Fourier Transform (FFT) convolution on said plurality of regions with a convolution kernel representing a geometric shape to produce an intermediate image;
performing an inverse FFT convolution on said intermediate image to produce a second image;
applying a blur operator on said second portion of said first image and preserving said first portion to produce a third image; and
combining said second image and said third image to produce a resultant image.
15. The non-transitory computer-readable storage medium of claim 14 , wherein said blur operator comprises a diffusion depth-of-field (DOF) solver, and wherein said resultant image presents a Bokeh effect.
16. The non-transitory computer-readable storage medium of claim 14 , wherein said Fast Fourier Transform (FFT) convolution converts said plurality of regions from a space domain to a frequency domain.
17. The non-transitory computer-readable storage medium of claim 14 , wherein said selecting said plurality of regions comprises: down-sampling said second portion of said first image to a reduced-resolution image, and applying a bright pass filter on said reduced-resolution image based on a luminance threshold.
18. The non-transitory computer-readable storage medium of claim 14 , wherein said method further comprises configuring a plurality of execution threads to perform said FFT convolution and said inverse FFT convolution respectively in parallel.
19. The non-transitory computer-readable storage medium of claim 14 , wherein said first portion corresponds to an in-focus subject represented in said first image, and wherein said second portion corresponds to a background represented in said first image.
20. The non-transitory computer-readable storage medium of claim 14 , wherein said convolution kernel represents a camera aperture shape with a size equal to a circle of confusion (CoC) at an infinite distance of said first image.