# Exposure Bracketing Techniques for Camera Document Image Enhancement
## 2 Technical Overview of Exposure Bracketing Techniques  
Exposure bracketing techniques can be divided into two groups [3]. The first group method is closely related to tone mapping. The basic idea behind it is to create a high dynamic range radiance map, first by combining all the low dynamic range (LDR) images (that is, images with different exposures) and after that, a mapping function is employed to transform the high dynamic range radiance map to a high dynamic range (HDR) image. For more details on HDR image generation, please refer to [3]. This processing chain is shown in Figure 2.  
In Figure 2, image registration is employed before mapping LDR image pixel values on the radiance map. The reason why image registration is needed is because when generating the multiple exposure images, there are always geometric disparities between them. Therefore, it is necessary to align them in a common coordinate system where the same pixels in different images share the same coordinate.  
Figure 1: Camera document images with different exposure times. (**a**) exposure time: 1/800 s (under-exposed). (**b**) exposure time: 1/320 s (well-exposed). (**c**) exposure time: 1/40 s (over-exposed).  
The second category of exposure bracketing techniques is called exposure fusion, as shown in Figure 3. Compared to the tone mapping method, this method does not generate a radiance map based on the input of multiple exposure images. Instead, it first selects or calculates a weighting factor for each pixel in multiple LDR images based on some quality criteria and then generates an HDR image by padding the selected pixel or weighted sum of pixels of multiple images. This method usually follows the following processing chain:  
In the context of document image exposure bracketing, the literature we found is really limited. The only paper that discloses document image exposure bracketing techniques can be found in paper [4], where an adaptive image fusion was used. However, there are two limitations in this paper: (1) the author assumes that document images are captured with a fixed camera and hence there is no need to perform image registration. As we will discuss in the next section, projective distortion often happens when capturing document images and there are geometric disparities among the captured images. (2) The author discusses and compares different image fusion strategies, however tone mapping techniques are missing from their comparison. We think that it is necessary to incorporate tone mapping in the processing chain as it is one of the mainstream methods in exposure bracketing. It is true that there are several papers that discuss the document image registration problem. For example,  
Figure 3: Exposure fusion processing chain.  
Figure 2: Tone mapping processing chain.  
in paper [5], the classic key point feature descriptor-based image registration method was combined with mobile phone sensor data such as the accelerometer and gyroscope sensor data to perform image mosaic reconstruction. However, their registration is more suitable for the image mosaic reconstruction purpose while the registration method that we used is more suitable for exposure bracketing.  
As both categories of methods employ image registration as a preprocessing step, it is necessary to first find a proper image registration method in the context of document image exposure bracketing.