基于变化光源方向多图像的植物叶片表观三维模拟

为了真实准确地模拟植物叶片表观颜色,提出一种基于多图像的叶片表观模拟方法。首先搭建基于线性光源的表观图像采集系统,用以获得400张视线角度固定、光源方向变化的叶片图像集合;采用拟合方法自动地从400张图像中获得整个叶片表面的表观特征参数,包括漫反射强度、高光反射强度和粗糙度;利用该拟合方法对线性光源移动条件下理想物体的各种反射特征的变化情况进行仿真计算,然后针对叶片图像中的每个像素寻找与仿真计算结果最接近的表观模型参数作为拟合结果。通过该拟合方法,可将叶片表面上各个位置的表观参数合成3张表观参数图像,采用基于点光源的实时光照方法测试最终的可视化模拟效果。从模拟结果中可以看出利用该文方法得到的结果能够真实地表现叶片自身的表观质感特性,相对于传统方法更加真实准确。

Three dismensional appearance simulation of plant leaves based on multiple images with light source change

Abstract: Three-dimensional (3D) Plant modeling and visualization is a key research issue in both digital plant and agricultural application. Leaf is one of the vital organs in a plant, so the 3D modeling and shading of plant leaves is an important and fundamental work for achieving the goals of digital plant. Appearance simulation of plant leaves is still a challenging issue because of its intricate underlying structure and complex and subtle interaction with light. Texture mapping using leaf photo is a common method for appearance simulation, however, it could bring noise caused by light environment and camera position in lighting simulation step. This paper presents a technique for simulating the appearance of plant leaves with multiple images. Our method can estimate the spatially-varying reflectance properties of plant leaf surface based on a few images, which capture leaves' appearance transition information with different light directions. An apparent image acquisition system using linear light source is built for capturing 400 images with a fixed camera viewpoint and a single direction of motion for the linear light source. This system is composed of a driving module, a linear source module, a background module and a camera. Using a linear light rather than a point light source as the illuminant, we can obtain a piece of area with more intensive illumination. With these image data, we develop a fitting method, which is able to estimate the diffuse color, specular color and specular roughness of each point on the leaf surface. In our method, the isotropic ward model is utilized as the appearance model for specifying that how the leaf surface reflects light. Our fitting technique first simulates the change of reflectance attributes of diffuse and specular reflectance lobes under moving linear light source. In this process, a rectangle is employed to simulate the linear light source and Monte Carlo integration method is used to calculate the radiation transmission process. When we have the simulating results, the appearance parameters of each pixel are determined by comparing its actual parameter values to the simulating results. By above fitting method, 3 kinds of spatially-varying appearance parameters are saved into 3 parameter images for rendering leaf appearance. For quickly shading, multipoint point light sources are used for simulating various illumination conditions instead of complex radiative transfer integral. Using appearance parameter images and shading method, static appearance or dynamic appearance transition of plant leaves can be generated realistically. From the results obtained by this method, we find that it can render more accurate and real appearance texture of leaves compared to traditional texture mapping methods. The advantages of our method are that the appearance parameter images for rendering have removed the light and viewport noise, and only contained the appearance material information. In order to prove this conclusion, we quantitatively analyze the reason for this advantage by some formula derivations in this paper. But for obtaining these advantages, our method needs more complex data acquisition process and parameter fitting algorithm, which will reduce the efficiency of simulation. For improving the efficiency of our method, 2 approaches are discussed in this paper, including reducing image resolution and fitting the specular parameters of the whole leaf by a few sample points. Our method can estimate some appearance parameters which are plant leaf own intrinsic properties. We believe this characteristic will make these appearance parameters used not only for visualization, but also as some important phenotypes instead of so-called color data. In the future work, we will extend the application of our method in agriculture, such as monitoring plant growth status with the appearance parameters, or analyzing the differences among plant varieties.