Upload test images taken under controlled settings to compare lenses or sensors in order to evaluate quality.
Advanced Lens Analyzer Pro
Enhanced Analysis with Sharpness, MTF, and Advanced Color Metrics
Drop lens test images here or click to select
Upload multiple images for comparative lens analysis
Now with advanced sharpness, edge detection, and enhanced color analysis
In order to use this tool to evaluate your equipment you should Upload a set of images that were taken with various lenses or camera sensors under identical controlled conditions. Each image filename should uniquely identify the lens or camera sensor and/or camera and lens settings that you are testing. Ex 1: R5-Canon-EF-100m-f2-8L-Af5-6-ISO100-S1-160.jpg
Ex 2: R5-Canon-EF-100m-f2-8L-Af8-ISO100-S1-160.jpg
This way you can keep track of which calera, lens and setting each result corresponds with.
The resulting csv file which you can download contains an analysis and score for each image which you can then interpret manually or upload to an AI chatbot like ChatGPT along with the explanation of the process (which you can find below) of this test in order to obtain a natural language summary of the test.
This webapp is a work-in progress which automatically analyzes each image uploaded to extract several objective metrics:
Overview
The Advanced Lens Analyzer Pro uses a comprehensive computer vision and image analysis methodology to objectively evaluate photographic lens performance. This system goes beyond subjective impressions to provide quantitative, repeatable measurements of optical quality.
Test Setup Requirements
Controlled Environment
Identical lighting conditions across all test shots
Same subject matter (recommended: neutral test chart or standardized scene)
Consistent exposure settings (aperture, shutter speed, ISO)
Same camera body to eliminate sensor variables
Tripod-mounted to ensure consistent framing and eliminate camera shake
Image Requirements
High-resolution images (preferably RAW processed to JPEG at highest quality)
Same focal length testing when comparing zoom lenses
Consistent focus (manual focus on same target preferred)
Uniform file formats and compression settings
Analysis Methodology
1. Sharpness Analysis (25% of Final Score)
Method: Laplacian Edge Detection
Converts image to grayscale for luminance-based analysis
Applies Laplacian filter to detect edges and fine detail
Calculates variance of edge response (higher = sharper)
Why this matters: Direct correlation to resolving power and lens acutance
2. Brightness & Exposure Analysis (15% of Final Score)
Method: Percentile-Based Luminance Measurement
Analyzes full brightness histogram of all pixels
Uses P1, P5, P95, P99 percentiles instead of single-pixel extremes
Measures light transmission efficiency
Why this matters: Indicates lens coating quality and light-gathering ability
3. Contrast Analysis (20% of Final Score)
Method: Tonal Range Assessment
Calculates P95-P5 percentile spread for robust contrast measurement
Avoids noise from extreme pixel outliers
Measures micro-contrast and tonal separation
Why this matters: Critical for image "pop" and three-dimensional rendering
4. Dynamic Range Analysis (15% of Final Score)
Method: Full Tonal Range Measurement
P99-P1 spread indicates total dynamic range capability
Detects highlight clipping and shadow blocking
Measures lens flare resistance
Why this matters: Determines lens ability to handle high-contrast scenes
5. Field Evenness Analysis (15% of Final Score)
Method: 9-Region Brightness Mapping
Divides image into center, corners, and mid-edge regions
Compares regional brightness variations
Detects vignetting and illumination falloff
Why this matters: Professional lenses should maintain uniform illumination
6. Color Neutrality Analysis (10% of Final Score)
Method: Advanced Color Space Analysis
5-cluster K-means color clustering for better discrimination
Chromaticity coordinate analysis (CIE color space)
Color bias detection in R/G/B channels
Why this matters: Accurate color reproduction is essential for professional work
Scoring System
Final Score Calculation
Final Score = (Sharpness × 0.25) + (Contrast × 0.20) + (Brightness × 0.15) + (Field Evenness × 0.15) + (Dynamic Range × 0.15) + (Color Neutrality × 0.10)
Score Interpretation
90-100%: Exceptional professional lens
80-89%: Excellent professional quality
70-79%: Very good, suitable for professional work
60-69%: Good consumer/enthusiast lens
50-59%: Adequate for casual use
Below 50%: Poor optical performance
Technical Advantages Over Subjective Testing
Repeatability: Same lens will always produce same scores under identical conditions
Objectivity: Eliminates reviewer bias and subjective preferences
Quantification: Provides specific numerical values for comparison
Comprehensive: Evaluates multiple optical characteristics simultaneously
Scientific: Based on established computer vision and optical measurement techniques
Limitations & Considerations
Test subject dependency: Results optimized for the specific scene/chart photographed
Aperture specificity: Each f-stop should be tested separately
Focus accuracy critical: Manual focus precision affects sharpness measurements
Environmental factors: Temperature, humidity can affect some measurements
Compression artifacts: JPEG compression may influence fine detail analysis
Applications
Professional Use
Lens purchasing decisions
Quality control in lens manufacturing
Rental house lens evaluation
Insurance documentation
Educational Use
Understanding optical principles
Comparative lens studies
Technical photography education
Optical engineering demonstrations
This methodology provides objective, scientific analysis of lens performance characteristics that correlate strongly with real-world photographic quality and professional optical testing standards.
Why It’s Useful
This tool lets me look at entire sets of images in a quantitative way, rather than relying purely on visual or subjective judgment. For example, when testing lenses, sensors, or different processing pipelines, I want to know objectively how exposure shifts, highlight handling, or color casts change. It streamlines comparison and ensures that my analysis is consistent and repeatable—key for both technical validation and large-scale image quality projects.
How I Thought of It
I created this because I wanted to bridge the gap between hands-on photography and technical analysis—especially when comparing equipment or processing flows. Manual scoring is slow and inconsistent, but a simple script lets me quickly flag outliers, confirm trends, and focus my subjective evaluation where it matters most. It’s also a practical foundation to build more advanced metrics, like sharpness, noise, or color accuracy, as my testing needs evolve.
Copy and use this AI Prompt below in conjunction with the csv file provided by this test in your favorite AI chatbot tool to get an simplified natural language explanation of the test results
AI Analysis Prompt for Lens Test Results
You are a professional lens analyst and optical testing expert. I will provide you with CSV data from scientific lens testing using advanced computer vision analysis. Please analyze the results and provide detailed, natural language explanations.
About the Test Methodology
Test Setup: All lenses were photographed under identical controlled conditions (same lighting, subject, camera body, tripod setup) to ensure fair comparison. Each image was analyzed using advanced computer vision algorithms.
Analysis Metrics Explained:
Core Performance Scores (0-1 scale, higher = better):
final_score: Overall lens performance (weighted average of all metrics)
score_sharpness: Edge detection analysis using Laplacian variance (25% of final score)
score_contrast: Tonal range using P95-P5 percentile spread (20% of final score)
score_brightness: Light transmission efficiency (15% of final score)
score_dynamic_range: P99-P1 tonal range capability (15% of final score)
score_field_evenness: Vignetting/illumination uniformity across image (15% of final score)
score_color_shift: Color neutrality, lower = more neutral (10% of final score)
score_extremes: 1 if pure black and white present (dynamic range indicator)
Technical Measurements:
sharpness_score: Raw Laplacian variance value (higher = sharper edges)
average_brightness: Mean luminance (0-255)
median_brightness: 50th percentile brightness
std_brightness: Brightness standard deviation (higher = more contrast)
p1_brightness, p99_brightness: 1st and 99th percentile (shadow/highlight detail)
p5_brightness, p95_brightness: 5th and 95th percentile (usable tonal range)
dynamic_range: P99-P1 spread (total tonal range)
Color Analysis:
color_bias_r, color_bias_g, color_bias_b: Channel deviation from neutral gray
chromaticity_x, chromaticity_y: CIE color space coordinates (0.333, 0.333 = neutral)
Regional Analysis (Vignetting Detection):
center_brightness: Central region luminance
tl_brightness, tr_brightness, bl_brightness, br_brightness: Corner region luminance
Vignetting assessment: Compare center vs corner brightness differences
File Information:
filename: Original image file with lens identification
file_size_kb: File size in kilobytes
dimensions: Image resolution
Your Analysis Task
For the provided CSV data, please:
1. Individual Lens Analysis
For each lens (row in CSV), provide a natural language summary covering:
Overall performance ranking and final score interpretation
Sharpness characteristics - is this a sharp or soft lens?
Optical strengths - what does this lens do well?
Optical weaknesses - where does this lens fall short?
Professional suitability - recommended use cases
Comparison to group average - how does it rank against other tested lenses?
2. Group Analysis & Insights
Provide broader observations:
Best overall performer and why
Sharpest lens based on edge detection scores
Best for portraits (good sharpness + pleasing characteristics)
Best wide-angle performance (if applicable)
Best telephoto performance (if applicable)
Most neutral color rendering
Worst performers and their specific issues
Vintage vs modern lens trends (if both present)
Zoom vs prime lens differences (if applicable)
Value recommendations - best performance per dollar (if price known)
3. Technical Insights
Sharpness distribution across the lens group
Common optical issues detected
Field evenness patterns (vignetting trends)
Color rendering consistency across lenses
Dynamic range leaders and limitations
Response Format
Structure your response as:
EXECUTIVE SUMMARY
[Brief overview of test results and key findings]
INDIVIDUAL LENS ANALYSIS
[For each lens, detailed performance breakdown]
GROUP INSIGHTS & RANKINGS
[Comparative analysis and recommendations]
TECHNICAL OBSERVATIONS
[Advanced optical analysis and trends]
Please write in a professional but accessible tone, suitable for both photography enthusiasts and professionals. Use specific numerical references from the data to support your analysis, but explain technical concepts clearly.
Now analyze the attached CSV data using this framework.