A high-resolution surface wave velocity spectrum, also known as dispersion image, is of paramount importance for any seismic survey to accurately predict subsurface earth's properties. The presence of diversified noise in the field acquisition and dissimilar attenuation due to mechanical and radial damping makes it challenging for different wavefield transformation algorithm to produce a detailed and precise velocity spectrum. Standard seismic data preprocessing technique like trace

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... n or bandpass filter fails to address all issues appropriately. Here we have presented a new superior preprocessing technique that can eradicate most of the shortcomings adequately. Experimental field data and published results are used to demonstrate the accuracy of the proposed method. The proposed method also found to produce superior results when compared against the popular commercially available software package Surfseis 6. Overall, the proposed method improves the quality of the velocity spectrum significantly, and it produces a sharper dispersion image even for the extremely noisy data. The work presented here enhances our ability to interpret the surface wave data precisely and help explore accurate properties of the subsurface earth.