# A High-Dynamic-Range Optical Remote Sensing Imaging Method for Digital TDI CMOS
## 1 Introduction  
In the field of image sensor applications for optical remote sensing, the complementary metal-oxide-semiconductor (CMOS) has been widely used by virtue of its simple circuit structure, low power consumption, and low cost. However, restricted by the structure of active pixel sensors (APS), electric charges cannot be transferred across pixels in the CMOS [1; 2; 3]. Therefore, for the pushbroom imaging cameras in a low Earth orbit, the CMOS cannot complete multi-stage signal superposition in the charge domain as with time delay integration charge coupled device (TDI CCD). In recent years, the Skysat series [4] and Jilin-1 [5] satellites have used digital TDI technology to achieve pushbroom imaging with array CMOSs, which significantly reduced manufacturing costs and shortened the development cycle. With special design and compensation algorithms, digital TDI CMOSs approximate TDI CCDs in terms of sensitivity, ground sampling distance, and other measures of performance. However, the superposition of multi-stage images in the digital domain multiplies the read noise and dark noise. Thus, the details of dark or low-contrast targets are usually drowned out, making the imaging dynamic range a significant shortcoming of the digital TDI CMOS. Researchers have always pursued high-dynamic-range imaging (HDRI) of the remote sensing camera, regardless of using CCDs or CMOSs as the image sensors [6; 7; 8; 9; 10; 11; 12]. The reason is that thereflectivity of different targets on the ground varies greatly. For example, the strong contrast between the roof and the shadow-covered area of a high building may cause the irradiance span to surpass the dynamic range of camera. This may cause the low brightness targets to be drowned out by noise. The high brightness targets may make the corresponding pixels reach saturation or even overflow. An example is shown in Figure 1. The roofs in the red rectangle have reached saturation, while the shadowed targets in the blue rectangles are still too dark to be seen clearly. Thus, to apply the digital TDI CMOS in remote sensing, we should perform an in-depth analysis of its information transmission model, and explore the point of penetration at which to perform effective improved methods. If handled well, these methods can help to achieve the goal of HDRI, which is of great significance. From the perspective of definition, to improve the imaging dynamic range of the camera, the direct measures can be divided into two aspects. One aspect is based on increasing the full well capacity of the pixels, and the other is to reduce the noise. However, restricted by the current manufacturing level of the CMOS, it is difficult for these two parameters to meet higher requirements [7]. Therefore, we must explore other methods beyond the sensor itself. As is introduced in the second part of this paper, before delivering the final image, the digital TDI CMOS allows us to obtain and process the intermediate images of all of the different TDI stages, which are not available in TDI CCD. Among measures to improve the dynamic range in image processing, image enhancement and multi-exposure image fusion are typical and effective methods. In traditional image enhancement methods, such as histogram equalization (HE) [8] and gamma correction [9], non-linear gray value mapping is used to adjust the histogram of image globally. This actually changes the gray distribution so as to reveal the hidden information, which cannot be seen by the human eye. [PERSON] [10] proposed a variant of HE using Gaussian mixture modeling to achieve automatic image equalization. However, these global operators do not contain the subdomain information of images, so that their effect is limited, especially for targets with a low illumination level or low contrast in the high-contrast scenes. To cope with this problem, researchers have proposed some adaptive regional gray-scale adjustment methods. [PERSON] [11] divided the image histogram and assigned specific gray level ranges for each partition before equalizing them separately.