You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: What is the Truth: A Survey of Video Compositing Techniques 
Chapter Title:  IV. BLENDING 
1. Abstract of Cited Paper (BIB001):  In this paper, we present a user-friendly system for seamless image composition, which we call drag-and-drop pasting. We observe that for Poisson image editing [Perez et al. 2003] to work well, the user must carefully draw a boundary on the source image to indicate the region of interest, such that salient structures in source and target images do not conflict with each other along the boundary. To make Poisson image editing more practical and easy to use, we propose a new objective function to compute an optimized boundary condition. A shortest closed-path algorithm is designed to search for the location of the boundary. Moreover, to faithfully preserve the object's fractional boundary, we construct a blended guidance field to incorporate the object's alpha matte. To use our system, the user needs only to simply outline a region of interest in the source image, and then drag and drop it onto the target image. Experimental results demonstrate the effectiveness of our "drag-and-drop pasting" system. 
2. Abstract of Cited Paper (BIB002):  Our goal is to develop tools that go beyond frame-constrained manipulation such as resizing, color correction, and simple transitions, and provide object-level operations within frames. Some of our targeted video editing tasks includes transferring a motion picture to a new still picture, importing a moving object into a new background, and compositing two video sequences. The challenges behind this kind of complex video editing tasks lie in two constraints: 1) Spatial consistency: imported objects should blend with the background seamlessly. Hence pixel replacement, which creates noticeable seams, is problematic. 2) Temporal coherency: successive frames should display smooth transitions. Hence frame-by-frame editing, which results in visual flicker, is inappropriate. Our work is aimed at providing an easy-to-use video editing tool that maximally satisfies the spatial and temporal constraints mentioned above and requires minimum user interaction. We propose a new framework for video editing in gradient domain. The spatio-temporal gradient fields of target videos are modified and/or mixed to generate a new gradient field which is usually not integrable. We propose a 3D video integration algorithm, which uses the variational method, to find the potential function whose gradient field is closest to the mixed gradient field in the sense of least squares. The video is reconstructed by solving a 3D Poisson equation. We derive an extension of current 2D gradient technique to 3D space, yielding in a novel video editing framework, which is very different from all current video editing software. 
3. Abstract of Cited Paper (BIB003):  Gradient-domain compositing is an essential tool in computer vision and its applications, e.g., seamless cloning, panorama stitching, shadow removal, scene completion and reshuffling. While easy to implement, these gradient-domain techniques often generate bleeding artifacts where the composited image regions do not match. One option is to modify the region boundary to minimize such mismatches. However, this option may not always be sufficient or applicable, e.g., the user or algorithm may not allow the selection to be altered. We propose a new approach to gradient-domain compositing that is robust to inaccuracies and prevents color bleeding without changing the boundary location. Our approach improves standard gradient-domain compositing in two ways. First, we define the boundary gradients such that the produced gradient field is nearly integrable. Second, we control the integration process to concentrate residuals where they are less conspicuous. We show that our approach can be formulated as a standard least-squares problem that can be solved with a sparse linear system akin to the classical Poisson equation. We demonstrate results on a variety of scenes. The visual quality and run-time complexity compares favorably to other approaches. 
4. Abstract of Cited Paper (BIB004):  Whether you're a novice compositor or a well-versed one moving over from After Effects or Shake, this is THE book for you to learn the ins and outs of the powerful compositing software, Nuke. In addition to covering all of the menus, buttons, and other software-specific topics, it also offers critical lessons in compositing theory, including working in 2.5D and stereoscopic 3D. Through a tutorial-based approach, augmented by video footage and image files provided on the companion DVD, this book will have you up and running in Nuke in just hours. The book features over 300 4-color images, industry insider sidebars, as well as an entire chapter dedicated to real-world Nuke case studies. 
5. Abstract of Cited Paper (BIB005):  Reconstruction and repairing damaged parts after object removal of digital video is an important trend in artwork restoration. Video completion is an active subject in video processing, which deals with the recovery of the original data. Most previous video completion approaches consume more time in extensive search to find the best patch to restore the damaged frames. In addition to that, visual artifacts appear when the damaged area is large. In this paper, we present a fast and efficient video completion method without the extensive search process. The proposed method is based on the object prior positions and the temporal continuity of the video frames. The proposed method is fast and maintains the spatial and temporal consistency. In addition to that, it can handle the object size and posture change, non periodic motion, and non stationary background.

Literature Review:
For blending two or more layers, there are many techniques are used. The alpha blending is considered the simplest technique for the blending process  as shown in the following equation where F C is the final composited frame, B is the generated mask, L 1 is the first layer, and L 2 is the second layer. In alpha blending, there is no color correction, that leads to unrealistic blending of layers with different lighting conditions. The color correction process handles those differences. In the alpha blending, there are two types for video compositing: Layer-based compositing and node-based compositing BIB005 . In layer-based compositing, the footages are stacked as layers in a specific order. Many software packages use layer-based compositing technique for compositing two or more videos, such as Adobe After Effects. In node-based compositing, each footage is represented as a node. The compositing process is represented as a node-tree or a flow chart. This type of compositing is used for complex tasks. On the other hand, there are other techniques were presented for achieving a realistic blending. Those techniques clone selected pixels from an image to another one in a natural appearance. These techniques do not require color correction process for fixing the different lighting conditions between the two images. This task is performed within the blending process. Adobe Photoshop presents a tool for seamless cloning that is called Healing Brush tool  . Healing Brush tool blends two images using a fourth-order Partial Differential Equation (PDE) for continuation of derivation that clones two images which have different textures on a natural look  . P. Pé rez et al. BIB001 Many cloning techniques improve the results of Poisson image editing, such as drag-and-drop pasting BIB002 , content-aware copying and pasting  , error-tolerant image compositing BIB004 , and Modified Poisson Blending (MPB) technique  . Gradient domain is used in video inpainting by H.Wang et al. BIB003 that is a framework for spatio-temporal video editing. The efficiency of inpainting techniques is measured using the human visual observation rather than numerical measurements BIB006 . Because of this reason, nobody can numerically prove which image blending technique is the best one. Fig. 12 shows examples of blending target images with source images using Healing Brush, Poisson image editing, error-tolerant image compositing, and MPB. Fig. 12 shows that, each technique fails in some cases and succeeds in other cases. In Sec. VI, a comparison among the performance of Poisson image editing, error-tolerant image compositing, and MPB techniques is presented.