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: A Survey of Image Compression Algorithms for Visual Sensor Networks 
Chapter Title:  Transform-Based DCT Algorithms 
1. Abstract of Cited Paper (BIB001):  With the projected significant growth in mobile internet and multimedia services, there is a strong demand for next-generation wireless appliances capable of image communication. However, wireless image communication faces significant bottlenecks including high energy and bandwidth consumption. Past studies have shown that the bottlenecks to wireless image communication can be overcome by developing adaptive image compression algorithms and dynamically adapting them to current channel conditions and service requirements [1,2].In this paper, we present the design of an adaptive hardware/software architecture that enables adaptive wireless image communication. Through intelligent co-design of the proposed architecture and algorithms, we achieve an architecture which enables not only power and performance efficient implementation, but also fast and efficient run-time adaptation of image compression parameters. To achieve efficient image compression and run-time adaptation, we characterized the adaptation needs of an adaptive image compression algorithm in terms of parameters, and implemented an adaptive hardware/software architecture capable of executing JPEC image compression with different parameters. We present experimental results demonstrating that the proposed architecture enables low overhead adaptation to current wireless conditions and requirements while implementing a low cost (energy and performance) implementation of adaptive image compression algorithms. 
2. Abstract of Cited Paper (BIB002):  Wireless video-surveillance networks are gaining increasing popularity due to the number of applications they make possible. We address the problem of designing a wireless video-surveillance network so as to optimize its performance. In particular, we investigate the possible trade-offs between energy consumption and image quality. We provide simulation results showing that video compression can be very beneficial in reducing data transmission costs, provided that the energy cost of video compression is low. Moreover, we discuss the impact of compression on image delay. 
3. Abstract of Cited Paper (BIB003):  This paper presents a 2-D DCT/IDCT processor chip for high data rate image processing and video coding. It uses a fully pipelined row---column decomposition method based on two 1-D DCT processors and a transpose buffer based on D-type flip-flops with a double serial input/output data-flow. The proposed architecture allows the main processing elements and arithmetic units to operate in parallel at half the frequency of the data input rate. The main characteristics are: high throughput, parallel processing, reduced internal storage, and maximum efficiency in computational elements. The processor has been implemented using standard cell design methodology in 0.35 ?m CMOS technology. It measures 6.25 mm2 (the core is 3 mm2) and contains a total of 11.7 k gates. The maximum frequency is 300 MHz with a latency of 172 cycles for 2-D DCT and 178 cycles for 2-D IDCT. The computing time of a block is close to 580 ns. It has been designed to meets the demands of IEEE Std. 1,180---1,990 used in different video codecs. The good performance in the computing speed and hardware cost indicate that this processor is suitable for HDTV applications. 
4. Abstract of Cited Paper (BIB004):  We present the design, implementation, and application of several families of fast multiplierless approximations of the discrete cosine transform (DCT) with the lifting scheme called the binDCT. These binDCT families are derived from Chen's (1977) and Loeffler's (1989) plane rotation-based factorizations of the DCT matrix, respectively, and the design approach can also be applied to a DCT of arbitrary size. Two design approaches are presented. In the first method, an optimization program is defined, and the multiplierless transform is obtained by approximating its solution with dyadic values. In the second method, a general lifting-based scaled DCT structure is obtained, and the analytical values of all lifting parameters are derived, enabling dyadic approximations with different accuracies. Therefore, the binDCT can be tuned to cover the gap between the Walsh-Hadamard transform and the DCT. The corresponding two-dimensional (2-D) binDCT allows a 16-bit implementation, enables lossless compression, and maintains satisfactory compatibility with the floating-point DCT. The performance of the binDCT in JPEG, H.263+, and lossless compression is also demonstrated.

Literature Review:
Before reviewing the main DCT-based algorithms found in the literature, we briefly describe the principal idea behind DCT. The DCT is a technique for converting a signal into elementary frequency components. The image is decomposed into several blocks, and for each block, DCT is mathematically expressed as a sum of cosine functions oscillating at different frequencies. Since we concentrate on images, we consider only the two dimensional representation of DCT (2D DCT), which can be obtained from the cascade of two 1D DCTs. The well-known compression scheme based on DCT is the standard JPEG BIB001 . In this survey paper, JPEG is analyzed in the context of power-constrained application. Other variants of the compression scheme based on DCT are proposed in the literature to enhance JPEG features, such 4 ISRN Sensor Networks as minimizing the blocking artifacts, minimizing the complexity at the encoder and/or the decoder, and increasing the compression ratio. Since the DCT transform consumes the most power within a DCT-based compression scheme (more than 60% of the computation cost of the JPEG algorithm BIB002 ), many attempts to decrease its computational complexity have been suggested in the literature. Some of them, which are helpful for VSN designers, are cited as follows. (1) Parallel and pipelined implementation of multidimensional DCT: the authors in BIB004 use a parallel and pipelined row-column decomposition method based on two 1D DCT processors and an intermediate buffer. The proposed architecture allows the main processing elements and arithmetic units to operate in parallel, which reduce both the computational complexity and the internal storage, and allows a high throughput BIB004 . The same idea is explored in  with the integer cosine transform (a reduced computational complexity version of DCT) to further reduce the computational complexity of the whole system. To the best of our knowledge, the exploration of parallel and pipelined implementation of 2D DCT has not yet been investigated in VSN. (2) Working with fixed-point instead of the more complicated floating-point DCT: compared to fixedpoint DCT, working with the floating-point DCT exhibits high energy consumption. For illustration purpose, let us consider the following example from BIB003 . Encoding a grayscale QCIF image at 1 bitper-pixel using the processor StrongARM SA1110 with JPEG-integer-point DCT requires 2.87 mJ. The same operation using floating-point DCT necessitates more than 22 mJ. This justifies the possible choice of fixed-point DCT over floating-point DCT in case of VSN. (3) Converting the greedy operations such as multiplications into light operations: indeed, DCT can be implemented using light operations such as shifts and additions only. For instance in BIB005 , a multiplierless version of DCT based only on shift and addition operations is suggested. This scheme enables low-cost and fast implementation compared to the original DCT, due to the elimination of the multiplication operations BIB005 . In the following section, we introduce JPEG, the wellknown DCT-based scheme, its advantages and shortcoming, as well as a discussion about its possible application in VSN.