The field of digital image compression has been intensively explored to obtain ever improved performance corresponding to a given bit budget. The DCT-based JPEG standard remains to be one of the most popular image compression standards due to its reasonable coding performance, fast implementations, friendly low-cost architecture. flexibility and adaptivity on block level. In this thesis, we consider the problem of low bit-rate image coding and present new approaches using adaptive strategies and optimization techniques for performance enhancement, while employing the DCT block-based JPEG standard as the main framework with several pre- and post-processing , steps. We propose an adaptive coding approach which involves a variable quality factor in the quantization step of JPEG compression to make the compression more flexible in respect to bit budget requirements. We also propose an adaptive sampling approach based on variable down-'up-scaling rate and local image characteristics. In addition. we study an adaptive filtering approach in which the optimal filters coefficients are determined by making use of optimization methods and symmetric extension techniques. Simulation results are presented to demonstrate the effectiveness of the proposed techniques relative to recent works in the field of low bit-rate image coding.