Real time field depth analogy method based on fuzzy partition of graphics processor

Abstract

The invention discloses a real time field depth analogy method based on fuzzy partition of a graphics processor. The real time field depth analogy method based on the fuzzy partition of the graphics processor comprises the following steps of (1) converting a to-be-processed image into a file format which can be processed by a graphics processing unit (GPU), (2) processing specific information of the image, (3) carrying out partition blur processing to the image according to the specific information of the image, and deciding that the image adopts different fuzzy radius in different areas according to the specific information, and thus imitating a filed depth effect. Due to the facts that parallelism and programmable capacity of the GPU are fully used, a scene is saved as a texture in render, and a large amount of algebraic operation is transferred from a central processing unit (CPU) to the GPU, the real time field depth analogy method based on the fuzzy partition of the graphics processor not only releases the CPU, but also reduces amount of communication between the CPU and the GPU, and greatly improves imitation speed of the filed depth. Due to the fact that a partition fuzzy algorithm is directly used for processing an original image, a step of fusion of a traditional algorithm fuzzy image and the original image is saved, and accuracy of filed depth imitation is further improved. The image is clear and exquisite, close to a field depth effect picture which is shot by an actual camera, and the real time field depth analogy method based on the partition blur of the graphics processor is applicable to a virtual reality system.

Description

technical field [0001] The invention relates to a real-time depth-of-field simulation method based on graphics processor partition blur. Background technique [0002] Depth of field refers to the object distance range measured along the axis of the imaging depth of field camera that can obtain clear images in front of the camera lens or other imagers. After the focus is completed, a clear image can be formed in the range before and after the focus. This distance range before and after is called the depth of field. There is a certain length of space in front of the lens (before and after the focusing point). When the subject is located in this space, its image on the negative film is just between the two diffusion circles before and after the focus. The length of the space where the subject is located is called the depth of field. In other words, the image blur of the subjects in this space on the negative surface is within the limit of the permissible circle of confusion, ...

AI Technical Summary

Problems solved by technology

However, the depth of field effect obtained by multiple renderings is heavy and lacks realism

[0007] c) Reverse ray tracing: This type of algorithm is limited to geometric scenes and uses real lens models, so the speed is difficult to meet the requirements of virtual reality systems

[0008] At present, many algorithms require a lot of calculations or lack precision, and a large number of algebraic operations of the traditional depth-of-field algorithm are completed by the CPU, which greatly limits the speed of depth-of-field simulation; steps, reducing the accuracy of the depth-of-field simulation

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