Veni Vidi Vici, A Three-Phase Scenario For Parameter Space Analysis in Image Analysis and Visualization

TL;DR

This paper introduces Veni Vidi Vici, an interactive visualization framework for analyzing and optimizing parameters in large-scale image analysis, reducing human effort and enhancing understanding of algorithm workflows.

Contribution

It presents a novel three-phase iterative approach and a prototype visualization tool for parameter space analysis in image processing, addressing current challenges in automation and standardization.

Findings

Effective visualization of parameter-output relationships.

Reduced user involvement in parameter optimization.

Potential for discovering new algorithms and workflows.

Abstract

Automatic analysis of the enormous sets of images is a critical task in life sciences. This faces many challenges such as: algorithms are highly parameterized, significant human input is intertwined, and lacking a standard meta-visualization approach. This paper proposes an alternative iterative approach for optimizing input parameters, saving time by minimizing the user involvement, and allowing for understanding the workflow of algorithms and discovering new ones. The main focus is on developing an interactive visualization technique that enables users to analyze the relationships between sampled input parameters and corresponding output. This technique is implemented as a prototype called Veni Vidi Vici, or "I came, I saw, I conquered." This strategy is inspired by the mathematical formulas of numbering computable functions and is developed atop ImageJ, a scientific image processing program. A case study is presented to investigate the proposed framework. Finally, the paper explores some potential future issues in the application of the proposed approach in parameter space analysis in visualization.