Abstract: Imaging-based diagnosis, for example, cell-based phenotypical differences between cell populations and colonoscopy, may suffer due to varying shapes, sizes, and similarities between the targets and the image background. Here, we combine spectral refinement and texture analysis for target localization. The proposed assembly acquires cell phenotyping data and can locate a target immersed in an image background. Interestingly, a reduced searchable image area, as obtainable by the proposed mechanism, would also minimize the training cost of machine learning models applied in object classification for disease diagnosis.