本文以佳能50D为例,简单明了地介绍数字相机中机内滤光镜的使用技巧,以期对喜爱黑白摄影的摄影爱好者提供有益的帮助。

In this paper, the Canon 50D for example, simply introduce the use of techniques of digital camera machine inner, in order to provide useful help to those who are enthusiastic about black and white photography.

数字成像设备在传输、显示图像时需要进行设备的特性化处理，该过程是设备颜色管理中的重要环节。为了保证输出图像的色彩复现能力，高动态范围数字相机需要根据设备自身特性进行特性化。现有特性化过程一般针对8位数字相机，并且转换矩阵的标定较为复杂，容易产生系统误差，矩阵精度易受影响。针对上述问题，提出了一种高动态范围彩色数字相机颜色管理方法，利用相机输出图像与被摄目标的色彩属性建立了RGB色彩空间到CIE1931 XYZ色彩空间的映射关系，并采用最小二乘拟合法对映射矩阵进行标定，最终将相机的RGB色彩空间转换至sRGB标准色彩空间，解决了高动态相机的特性化问题。实验证明，该方法操作简单，设备通用性较强，拟合均方误差优于0.08，具有较好的鲁棒性。

Digital imaging devices require color space characterization while transferring or showing image between various devices which is a crucial part of color management for digital devices. In order to keep the color reproduction ability for output image, a high dynamic range digital (HDR) camera requires characterization based on the device properties. For existing characterization algorithms, which are in most cases for 8- bit- digital cameras, the processes of transformation matrix calibration are involved in some complex approaches, which are easy to cause system errors and influence the precision of color space transformation matrix. Accordingly, a color management approach was proposed for a high dynamic range colorful digital camera that using a color space mapping from camera RGB space to CIE1931 XYZ color space to estimate the function relation between two color spaces and using the least square method to achieve color matrix calibration. Eventually the camera RGB color

将双目视觉原理应用于高速铁路接触线的几何参数测量。采用2个数字相机同时采集接触线的2幅图像,通过对图像进行平滑去噪、二值化和边缘识别,确定接触线在2个相机中的成像位置,进而计算出接触线的高度和拉出值。通过实验验证了该方法在测量速度、测量精度和实现动态测量等方面的优点,对基于双目视觉的接触线检测仪器开发有实用价值。

The principle of binocular vision has been used to measure the geometric parameters of high speed railway contact wire in this paper. Two digital cameras were used to acquire two ima-ges of contact wire simultaneously,then the loca-tions of two images on two camera’s imaging plane were determined respectively by processing the im-ages using such methods as smoothing,binary,and edge recognition,and then the contact wire ’s height and its stagger can be calculated.By experi-ments it is verified that the method has such ad-vantages as quick measurement speed,high accura-cy,and suited to dynamic measurement.All these are meaningful for developing the detecting instru-ments of contact wire based on binocular vision principle.

为了满足实际项目需求,设计了一套基于FPGA结合CMOS图像探测器的轻小型彩色数字相机系统。根据项目特点,选用了一片Xilinx公司FPGA作为硬件设计平台,使用Verilog-HDL硬件描述语言并采用自上而下的模块化设计对整个系统进行硬件描述,对图像探测器时序驱动、输出图像格式重组、彩色图像恢复等功能进行了详细的设计。试验结果表明,所设计的图像采集系统在1 280*1 024模式、25 f·s-1的情况下可以实时稳定的实现彩色图像的显示与存储。

In order to meet the actual needs of the engineering project, light and compact real-time digital camera was designed based on FPGA combined with CMOS sensor. Based on the characteristics of the system, one Field Programmable Gate Array (FPGA) is chosen as the hardware design platform, and the whole circuit such as sensor timing, image reshaping and demosaicking are described with Verilog-HDL to perform the modularization design from top to bottom. Experimental results show that continuous and real-time 1 280*1 024 resolution data read-out could be achieved at speed 25 f·s-1.

自动对焦技术对于数字相机至关重要,它是获取清晰图像的重要手段。针对复杂环境下多目标场景图像,提出了一种基于光流场估计的自动对焦算法。通过计算输入图像序列的光流场,对场景中的运动目标进行检测,根据目标运动属性准确判断出感兴趣目标。改进了Brenner清晰度评价方法,利用目标的二维边缘梯度信息建立评价函数,并且通过非线性增益提高评价函数的灵敏度,减小了噪声对评价值的影响。实验证明,该算法能够在主辅目标景深比达50倍的情况下分辨出感兴趣主目标,并在方差为0.02的随机噪声干扰下能有效地评价图像的清晰度;此算法将Brenner等评价函数的峰值稳定余量提高了1至4倍,对于不同图像具有良好的鲁棒性,易于硬件实现。

Auto-Focus technique is a main approach to hunt clear images which plays an important role in digital camera application. According to several unknown target under complicated condition, a novel auto-focus algorithm was proposed based on optical flow estimation. By calculating the optical flow of each input frame, the moving targets in scene image were tested as well as according to the moving characteristic, the interested real target was judged. Brenner sharpness evaluation method was improved. Meanwhile the evaluation function was established using two dimensions edge-gradient information. The response sensitivity of evaluation function was also increased via nonlinear-gain coefficient the impact of noise on evaluation value was decreased. Experimental results show that the proposed method can distinguish the interested main target in 50 times depths of field of different targets and evaluate the definition of varied images with random noise in 0.02 variance value effectively. And i