The paper presents a hybrid method combining Singular Value Decomposition (SVD) with interpolation algorithms for efficient image compression and reconstruction. The method focuses on decomposing a specific submatrix of an image to reduce storage requirements while maintaining image quality through linear and bilinear interpolation processes. Numerical experiments demonstrate the effectiveness and efficiency of the proposed approach in achieving high compression ratios while preserving essential image features.