OBJECTIVE (1)H MRS typical studies lead to low-resolution maps (voxels size>1cm(3)). The low-resolution maps may involve the presence of two or more different tissues in a single voxel which gives partial volume effects. Such insufficient spatial resolution remains an obstacle for most routine clinical examinations and restricts the ability in the detection of small lesions. METHODS The proposed algorithm is based on the combination of three ideas: controlled sub-pixel shift, averaging, and initial pixel size reduction until the spectrum extinction because initial pixel size will determine the final spatial resolution. Frequency range limits are studied to determine the optimal window of spectral peak (WSP). This method is validated in-vitro and in-vivo. RESULTS The results in-vitro allowed us to consolidate the theoretical one. Results in-vivo are compared with the clinical protocol to demonstrate the increase in spatial resolution. The proposed method allowed us to reduce the pixel size to1/16 of its initial pixel size in total scan time (TS) of 17min 10s. We demonstrated that the optimal WSP is 80% of its initial value and the interpolation "Bilinear" has the minimum error. CONCLUSIONS A novel approach is established for processing images and reconstructing high-resolution map from low-resolution maps. We have presented a robust algorithm for high spatial resolution in-vivo (1)H MRS, and have achieved a super spatial resolution up to 0.034cm(3) to overcome the major technical challenges.