Efficient Image Compression Techniques Leveraging Wavelet Transform and Quantization

Image compression is a continuously evolving field, driven by the need for optimizing storage and transmission while maintaining image fidelity. This work explores a hybrid compression approach by integrating Discrete Wavelet Transform (DWT) and Vector Quantization (VQ), two lossy compression techniques, to enhance the efficiency of medical image processing. The proposed algorithm is evaluated across diverse image datasets to assess its universal applicability. Experimental results demonstrate that the combined approach achieves significant compression ratios while preserving critical image details, making it suitable for medical imaging applications. The study further discusses the impact of preprocessing techniques and how they can be tailored based on specific use cases, ensuring adaptability across various domains.