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: Wavelet Based Image Coding Schemes : A Recent Survey 
Chapter Title:  WAVELET BASED CODING SCHEMES 
1. Abstract of Cited Paper (BIB001):  A new image compression algorithm is proposed, based on independent embedded block coding with optimized truncation of the embedded bit-streams (EBCOT). The algorithm exhibits state-of-the-art compression performance while producing a bit-stream with a rich feature set, including resolution and SNR scalability together with a random access property. The algorithm has modest complexity and is extremely well suited to applications involving remote browsing of large compressed images. The algorithm lends itself to explicit optimization with respect to MSE as well as more realistic psychovisual metrics, capable of modeling the spatially varying visual masking phenomenon. 
2. Abstract of Cited Paper (BIB002):  This paper describes methods for adapting the scanning order through wavelet transform values used in the wavelet difference reduction (WDR) algorithm of Tian and Wells (1996). These new methods are called adaptively scanned wavelet difference reduction (ASWDR). ASWDR adapts the scanning procedure used by WDR in order to predict locations of significant transform values at half thresholds. These methods retain all of the important features of WDR: low-complexity, region of interest, embeddedness, and progressive SNR. They improve the rate-distortion performance of WDR so that it is essentially equal to that of the SPIHT algorithm of Said and Pearlman (1996) when arithmetic compression is not employed. When arithmetic compression is used, then the rate-distortion performance of the ASWDR algorithms is only slightly worse than SPIHT. The perceptual quality of ASWDR images is clearly superior to SPIHT. 
3. Abstract of Cited Paper (BIB003):  A low complexity wavelet based image coding algorithm for color image compression is presented. The key renovation of this algorithm is that a small number of symbol set was designed to convert the information from the wavelet transform domain into a compact data structure for each subband. The scheme works first by color space conversion, followed by uniform scalar quantization and data conversion where raster scanning order is performed for individual subband and quantized coefficients are converted into the symbol stream according to the designed symbol representation. Two different context lists in each subband are specified from the symbol stream and alternatively compressed by an adaptive arithmetic coder with high efficiency. Unlike zerotree coding or its variations which utilize the intersubband relationship into its own data representation, our work is a low complexity intrasubband based coding method which only addresses the information within the subband. The only extension is the termination symbols which carry the zero value information towards the end of the subband or across the subbands till the end of the image. Compared with the zerotree refined schemes, this algorithm results in competitive PSNR values and perceptually high quality images at the same compression ratio for color image compression. 
4. Abstract of Cited Paper (BIB004):  The standard separable 2-D wavelet transform (WT) has recently achieved a great success in image processing because it provides a sparse representation of smooth images. However, it fails to efficiently capture 1-D discontinuities, like edges or contours. These features, being elongated and characterized by geometrical regularity along different directions, intersect and generate many large magnitude wavelet coefficients. Since contours are very important elements in the visual perception of images, to provide a good visual quality of compressed images, it is fundamental to preserve good reconstruction of these directional features. In our previous work, we proposed a construction of critically sampled perfect reconstruction transforms with directional vanishing moments imposed in the corresponding basis functions along different directions, called directionlets. In this paper, we show how to design and implement a novel efficient space-frequency quantization (SFQ) compression algorithm using directionlets. Our new compression method outperforms the standard SFQ in a rate-distortion sense, both in terms of mean-square error and visual quality, especially in the low-rate compression regime. We also show that our compression method, does not increase the order of computational complexity as compared to the standard SFQ algorithm. 
5. Abstract of Cited Paper (BIB005):  This paper describes a new and efficient method for low bit-rate image coding which is based on recent development in the theory of multivariate nonlinear piecewise polynomial approximation. It combines a binary space partition scheme with geometric wavelet (GW) tree approximation so as to efficiently capture curve singularities and provide a sparse representation of the image. The GW method successfully competes with state-of-the-art wavelet methods such as the EZW, SPIHT, and EBCOT algorithms. We report a gain of about 0.4 dB over the SPIHT and EBCOT algorithms at the bit-rate 0.0625 bits-per-pixels (bpp). It also outperforms other recent methods that are based on "sparse geometric representation." For example, we report a gain of 0.27 dB over the Bandelets algorithm at 0.1 bpp. Although the algorithm is computationally intensive, its time complexity can be significantely reduced by collecting a "global" GW n-term approximation to the image from a collection of GW trees, each constructed separately over tiles of the image 
6. Abstract of Cited Paper (BIB006):  This letter proposes an efficient extension of the set partitioning embedded block (SPECK) algorithm to lossless multispectral image coding. Such a wavelet-based coder is widely referred to in the literature, especially for lossless image coding, and is considered to be one of the most efficient techniques exhibiting very low computational complexity when compared with other state-of-the-art coders. The modification proposed in this letter is simple and provides significant improvement over the conventional SPECK. The key idea is to join each group of two consecutive wavelet-transformed spectral bands during the SPECK coding since they show high similarities with respect to insignificant sets at the same locations. Simulation results, carried out on a number of test images, demonstrate that this grouping procedure considerably saves on the bit budget for encoding the multispectral images. 
7. Abstract of Cited Paper (BIB007):  Geometric wavelet is a recent development in the field of multivariate nonlinear piecewise polynomials approximation. The present study improves the geometric wavelet (GW) image coding method by using the slope intercept representation of the straight line in the binary space partition scheme. The performance of the proposed algorithm is compared with the wavelet transform-based compression methods such as the embedded zerotree wavelet (EZW), the set partitioning in hierarchical trees (SPIHT) and the embedded block coding with optimized truncation (EBCOT), and other recently developed "sparse geometric representation" based compression algorithms. The proposed image compression algorithm outperforms the EZW, the Bandelets and the GW algorithm. The presented algorithm reports a gain of 0.22 dB over the GW method at the compression ratio of 64 for the Cameraman test image.

Literature Review:
Wavelet compression schemes allow the integration of various compression techniques into one. With wavelets, a compression ratio of up to 300:1 is achievable  . A number of novel and sophisticated wavelet-based schemes for image compression have been developed and implemented over the past few years. Some of the most popular schemes are discussed in the paper. These include Embedded Zero Tree Wavelet (EZW)  , Set-Partitioning in Hierarchical Trees (SPIHT)  , Set Partitioned Embedded Block Coder (SPECK) BIB007 , Embedded Block Coding with Optimized Truncation (EBCOT) BIB002 , Wavelet Difference Reduction (WDR ) BIB003 , Adaptively Scanned Wavelet Difference Reduction (ASWDR)  , Space -Frequency Quantization (SFQ) BIB005 , Embedded Predictive Wavelet Image Coder (EPWIC)  , Compression with Reversible Embedded Wavelet (CREW) BIB001 , the Stack-Run (SR) BIB004 , the recent Geometric Wavelet (GW) BIB006 and improved GW BIB008 . Each of these 'state of the art' algorithms are dealt and discussed in detail in the sections below.