Pixel Visualizer

Pixel Visualizer

Md Saif Ahmad, Sunny Kumar, Manmohan Kumar, Akshit Chauhan, Vansh Sadana, Er. Deepika Sharma

Department of Computer Science and Engineering
Chandigarh University
Mohali, Punjab, India

Abstract—Pixel-based visualization techniques have gained recognition because of their ability to provide huge records even as they provide specified insights. However, their effectiveness is restricted while coping with sparse datasets and random data distribution. Single pixels, whether or not remoted in vacant regions or amidst a complex array of differently coloured pixels, maybe without difficulty overlooked. Additionally, in the elaborate information, tendencies and memorable styles can be concealed. This paper explores diverse procedures for reinforcing pixel-primarily based visualizations, inclusive of strategies like halos, history colouring, distortion, and hatching. The assessment considers their efficacy in improving person pixels, figuring out traits, and highlighting extensive styles. Examples from diverse domains, specifically record evaluation, genome analysis, and geospatial evaluation, exhibit the wide applicability of these strategies and the pointers derived from the evaluation.

Keywords— detailed insights, sparse datasets, vacant regions, trends, notable patterns, enhancing techniques, halos, hatching, efficacy, genome analysis, applicability.