Frame transfer CCDs for digital still cameras: concept, design, and evaluation

Abstract

Digital still cameras are becoming a widely used alternative for conventional silver-halide cameras. This paper presents first the concept of frame-transfer CCD imagers designed for consumer digital cameras. Next, the different modes of operation are explained in detail and compared with alternative approaches. Finally, extensive evaluation results on four different imagers using this new concept are presented. It will be demonstrated that the flexible modes of operation, the high dynamic range, and excellent optical properties of FT-CCDs make them very suited for this type of electronic imaging.

Vehicle Anti-halation Image Evaluation Method Based on Visible and Infrared Fusion

“…夜间会车时，滥用远光灯使驾驶员感到非常刺 眼，无法看清行车路线及行人，极易导致严重的交通 事故 [1] 。因此，研究汽车抗晕光有重要意义。传统的 光学原理抗晕光方法使暗处信息难以观察 [2] ；红外夜 视仪的图像无色彩、细节信息缺失严重 [3][4][5] ； "排洪" 面阵 CCD 图像传感器把高亮度的多余电荷排出存储 势阱，仅降低了晕光的亮度 [6] ；光积分时间不同的两 路可见光融合依然存在晕光现象 [7] 。可见光与红外融 合的抗晕光方法 [8] 结合可见光图像色彩细节信息丰 富、红外图像无晕光的优点，为解决夜间行车的晕光 问题提供了一种新途径，具有较好的应用前景，但现 有的无参考、全参考和基于视觉系统的评价方法都不 能准确地评价抗晕光融合图像的质量 [9] 。 其中，无参考图像评价方法通过客观指标评价融 合图像自身质量 [10] 。融合图像消除晕光后，晕光部位 的高亮度信息被剔除，导致反映亮度的均值降低；晕 光消除越彻底，明暗对比度越低，晕光处的纹理细节 反差越小，标准差和边缘强度越低。全参考图像评价 方法评价融合图像对原始图像的信息保留度 [11] 。例如 交叉熵，在融合图像非晕光部位，该指标能很好地反 映其对原始图像细节信息的保留度，但在晕光部位， 晕光消除越彻底，与可见光图像相似度越低。基于视 觉系统的评价方法考虑人眼的视觉效果 [12]…”

Night Vision Anti-Halation Algorithm of Different-Source Image Fusion Based on Low-Frequency Sequence Generation

“…The existing active anti-halation methods include sticking polarizing film on the front windscreen [2], infrared night vision imaging [3][4][5], an array of CCD image sensors with a pixel integration time independently controllable [6], two visible image fusions with different light integration times [7], etc. Among them, multi-exposure image fusion [8] and infrared and visible image fusion [9,10] have lower halation retention and better visual effects.…”

An Improved Fourier-Mellin Transform-Based Registration Used in TDI-CMOS

“…The mechanical or optical methods need high-precision mechanical or optical structure to compensate image motion, [10] studied a smart structure to control the vibration. However, this additional structure itself adds additional complexity and reduce reliability [11], [12]. The electronic methods compensate image motion by adjusting transfer time, which can only compensate the along-track-motion of very limited range.…”