Two-Dimensional Grayscale Image Processing Using Haar Wavelet Transform and EZW Algorithm

In this processing pipeline, we perform a series of operations on the input two-dimensional grayscale image to achieve improved results. Initially, we apply the lifting Haar wavelet transform to enhance the image's detail representation. This transform implementation typically involves splitting, predicting, and updating steps to produce wavelet coefficients that better capture high-frequency details, providing an improved foundation for subsequent processing stages. Subsequently, we employ the classic Embedded Zerotree Wavelet (EZW) algorithm to compress the wavelet coefficients. The EZW algorithm implementation utilizes zerotree coding to efficiently represent significant coefficients across different wavelet scales, reducing the image's storage requirements while preserving critical visual information through progressive bitplane encoding. Finally, we perform the inverse transformation to reconstruct the original image from the compressed wavelet coefficients. This reconstruction process involves decoding the EZW bitstream and applying the inverse Haar wavelet transform to restore the image. Through this comprehensive processing sequence, we achieve enhanced image quality with higher compression ratios, making it suitable for applications requiring efficient image storage and transmission.