Terrestrial Laser Scanning (TLS) technology heavily supports high-resolution visual documentation alongside precise engineering geometry. However, during multi-station surveys, we often encounter differences in brightness and tone. Due to varying lighting conditions and automatic exposure, the same surface may appear lighter in one scan and darker or differently toned in another. Although the geometry is accurate, this "color patchiness" hinders high-quality utilization in fields where color fidelity is critical. This phenomenon presents a critical challenge in monument and heritage preservation, where authentic documentation is a prerequisite, as well as in the film and gaming industries, where flawless models are required for a photorealistic experience. Additionally, the problem poses a serious obstacle to the application of XR (VR/AR/MR) technologies and modern Digital Twins: patchy coloring and inconsistent tones significantly hinder the accurate identification of objects and degrade the extraction of visual information. The goal of this research is to explore this radiometric problem and develop an algorithm capable of analyzing the color information of neighboring points and overlapping areas, and then "blending" them via software (color blending). The student’s task is to investigate the relationships between existing panoramic images and the point cloud, and to find a solution that smooths out these sharp transitions based on neighborhood relations. During the work, the student will gain in-depth knowledge of the fundamentals of terrestrial laser scanning and the modern toolkit of spatial data processing. One of the main pillars of the research is the development of programming skills, enabling the creation of automated data correction processes. This topic is an ideal choice for those interested in the intersection of geoinformatics, computer graphics, and the latest visualization technologies (Digital Twins, XR).