Professional RGB to LAB color converter calculator with mathematical formula, Python code examples, Excel implementation, and MATLAB support. Convert RGB (Red, Green, Blue) values to CIELAB color space using precise color science algorithms and equations.
Transform standard RGB color codes to perceptually uniform LAB color space with our advanced converter tool. Includes RGB to LAB conversion formula, Python OpenCV implementation, Excel functions, and MATLAB code for professional color space conversion workflows.
Experience our advanced RGB to LAB color conversion calculator with real-time preview, interactive controls, mathematical formula display, and instant CSS code generation for professional color space conversion workflows.
Understanding the RGB to LAB color space conversion formula is essential for implementing accurate color transformations. The conversion involves multiple mathematical steps and color space transformations.
// RGB Gamma Correction if (R <= 0.04045) R = R / 12.92 else R = pow((R + 0.055) / 1.055, 2.4) if (G <= 0.04045) G = G / 12.92 else G = pow((G + 0.055) / 1.055, 2.4) if (B <= 0.04045) B = B / 12.92 else B = pow((B + 0.055) / 1.055, 2.4)
X = 0.4124564 * R + 0.3575761 * G + 0.1804375 * B Y = 0.2126729 * R + 0.7151522 * G + 0.0721750 * B Z = 0.0193339 * R + 0.1191920 * G + 0.9503041 * B
// Normalize XYZ values Xn = X / 95.047 // D65 illuminant Yn = Y / 100.000 Zn = Z / 108.883 // Apply LAB function if (t > 0.008856) t = pow(t, 1/3) else t = (7.787 * t) + (16/116) L = 116 * fy - 16 a = 500 * (fx - fy) b = 200 * (fy - fz)
import numpy as np from skimage import color def rgb_to_lab_python(rgb): """ Convert RGB to LAB using Python RGB values should be in range [0, 255] """ # Normalize RGB to [0, 1] rgb_normalized = np.array(rgb) / 255.0 # Reshape for skimage rgb_image = rgb_normalized.reshape(1, 1, 3) # Convert to LAB lab_image = color.rgb2lab(rgb_image) return lab_image[0, 0] # Example usage rgb_color = [255, 128, 64] lab_color = rgb_to_lab_python(rgb_color) print(f"RGB{rgb_color} -> LAB{lab_color}") # Using OpenCV import cv2 def rgb_to_lab_opencv(rgb): rgb_array = np.uint8([[rgb]]) lab_array = cv2.cvtColor(rgb_array, cv2.COLOR_RGB2LAB) return lab_array[0][0]
function lab = rgb_to_lab_matlab(rgb) % Convert RGB to LAB in MATLAB % RGB values should be in range [0, 255] % Normalize RGB to [0, 1] rgb_norm = double(rgb) / 255; % Create RGB image rgb_img = reshape(rgb_norm, [1, 1, 3]); % Convert to LAB using MATLAB function lab_img = rgb2lab(rgb_img); % Extract LAB values lab = squeeze(lab_img); end % Example usage: rgb_input = [255, 128, 64]; lab_output = rgb_to_lab_matlab(rgb_input); fprintf('RGB[%d,%d,%d] -> LAB[%.2f,%.2f,%.2f]\n', ... rgb_input, lab_output); % Alternative manual implementation function lab = manual_rgb_to_lab(rgb) % Step 1: RGB to XYZ xyz = rgb_to_xyz(rgb); % Step 2: XYZ to LAB lab = xyz_to_lab(xyz); end
function rgbToLab(r, g, b) { // RGB to LAB conversion in JavaScript // Input: RGB values (0-255) // Output: LAB values // Step 1: Normalize RGB to [0,1] and apply gamma correction let rNorm = r / 255; let gNorm = g / 255; let bNorm = b / 255; // Gamma correction rNorm = rNorm > 0.04045 ? Math.pow((rNorm + 0.055) / 1.055, 2.4) : rNorm / 12.92; gNorm = gNorm > 0.04045 ? Math.pow((gNorm + 0.055) / 1.055, 2.4) : gNorm / 12.92; bNorm = bNorm > 0.04045 ? Math.pow((bNorm + 0.055) / 1.055, 2.4) : bNorm / 12.92; // Step 2: RGB to XYZ conversion (D65 illuminant) let x = rNorm * 0.4124564 + gNorm * 0.3575761 + bNorm * 0.1804375; let y = rNorm * 0.2126729 + gNorm * 0.7151522 + bNorm * 0.0721750; let z = rNorm * 0.0193339 + gNorm * 0.1191920 + bNorm * 0.9503041; // Step 3: XYZ to LAB conversion x = x / 0.95047; // D65 illuminant normalization y = y / 1.00000; z = z / 1.08883; const fx = x > 0.008856 ? Math.pow(x, 1/3) : (7.787 * x + 16/116); const fy = y > 0.008856 ? Math.pow(y, 1/3) : (7.787 * y + 16/116); const fz = z > 0.008856 ? Math.pow(z, 1/3) : (7.787 * z + 16/116); const L = 116 * fy - 16; const a = 500 * (fx - fy); const b = 200 * (fy - fz); return { L: L, a: a, b: b }; } // Example usage: const rgb = { r: 255, g: 128, b: 64 }; const lab = rgbToLab(rgb.r, rgb.g, rgb.b); console.log(`RGB(${rgb.r}, ${rgb.g}, ${rgb.b}) = LAB(${lab.L.toFixed(2)}, ${lab.a.toFixed(2)}, ${lab.b.toFixed(2)})`);
Our RGB to LAB color converter calculator stands out as the most comprehensive and accurate tool for designers, color scientists, and developers who need precise color space conversion with mathematical formulas, code examples, and professional-grade algorithms.
Experience instant RGB to LAB color conversion with live preview capabilities. Our advanced color science calculator uses precise mathematical formulas and algorithms to ensure accurate color space transformation with real-time equation display.
Access complete RGB to LAB conversion formulas with step-by-step mathematical equations. Understand the gamma correction, XYZ transformation matrix, and CIELAB calculation process with detailed formula explanations and scientific accuracy.
Get ready-to-use RGB to LAB conversion code in Python, MATLAB, JavaScript, and Excel formulas. Includes OpenCV Python implementation, scientific computing libraries, and professional programming examples for all platforms.
Implement RGB to LAB conversion directly in Excel with our custom formulas and functions. Perfect for batch processing, data analysis, and spreadsheet-based color conversion workflows with step-by-step Excel implementation guide.
Compatible with OpenCV Python library for computer vision applications. Includes cv2.COLOR_RGB2LAB examples, image processing workflows, and computer vision color space conversion implementations for research and development.
Professional-grade CIELAB color space conversion with D65 illuminant, gamma correction, and perceptually uniform color representation. Supports scientific research, colorimetry, and precise color analysis workflows.
Understanding how primary colors translate from RGB to LAB color space using mathematical formulas and equations is fundamental for designers, color scientists, and developers. These examples demonstrate the precision of LAB color representation with step-by-step formula calculations.
RGB to LAB formula example
RGB Input Values
rgb(255, 0, 0)
LAB Output Result
lab(53.24% 80.09 67.20)
Calculation Steps
XYZ: (41.24, 21.26, 1.93) �?LAB conversion
Mathematical conversion example
RGB Input Values
rgb(0, 255, 0)
LAB Output Result
lab(87.73% -86.18 83.18)
Python Code Example
cv2.cvtColor(rgb, cv2.COLOR_RGB2LAB)
CIELAB calculation result
RGB Input Values
rgb(0, 0, 255)
LAB Output Result
lab(32.30% 79.19 -107.86)
MATLAB Function
lab = rgb2lab(rgb_image)
The CIELAB (LAB) color space offers significant mathematical and perceptual advantages over RGB for professional color workflows, particularly in fields requiring precise color communication, scientific analysis, and perceptual uniformity calculations.
LAB color space is designed to approximate human vision using mathematical formulas that closely match human perception of lightness and color differences. The mathematical foundation makes it ideal for:
Unlike RGB which is device-dependent, LAB is a device-independent color model based on CIE standards, offering mathematical benefits for:
Our RGB to LAB converter calculator implements precise color science algorithms following international CIE standards for color transformation, mathematical formulas, and professional color management implementation across Python, MATLAB, Excel, and JavaScript platforms.
Represents the perceived lightness (0 = black, 100 = white) using CIE standard formula: L* = 116 * f(Y/Yn) - 16
Represents colors along the green to red axis using mathematical formula: a* = 500 * [f(X/Xn) - f(Y/Yn)]
Represents colors along the blue to yellow axis using equation: b* = 200 * [f(Y/Yn) - f(Z/Zn)]
Convert RGB colors to HSL format with mathematical formulas for intuitive color manipulation and web design.
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The RGB to LAB conversion formula involves two main steps: First, RGB values are converted to XYZ color space using gamma correction and matrix transformation. Then, XYZ values are converted to CIELAB using the formulas: L* = 116 * f(Y/Yn) - 16, a* = 500 * [f(X/Xn) - f(Y/Yn)], and b* = 200 * [f(Y/Yn) - f(Z/Zn)], where f(t) = t^(1/3) if t > 0.008856, otherwise f(t) = (7.787 * t) + (16/116).
To convert RGB to LAB in Python using OpenCV, use: lab_image = cv2.cvtColor(rgb_image, cv2.COLOR_RGB2LAB)
. For individual color values, create a numpy array: rgb_array = np.uint8([[[r, g, b]]]); lab_array = cv2.cvtColor(rgb_array, cv2.COLOR_RGB2LAB)
. The result gives LAB values where L ranges 0-100, and a,b range approximately -127 to 127.
For Excel RGB to LAB conversion, create formulas for each step: (1) Gamma correction: =IF(A1/255<=0.04045,(A1/255)/12.92,POWER((A1/255+0.055)/1.055,2.4))
, (2) RGB to XYZ matrix multiplication, (3) XYZ normalization, and (4) LAB calculation: =IF(Y_norm>0.008856,116*POWER(Y_norm,1/3)-16,903.3*Y_norm)
for L*, with similar formulas for a* and b*.
In MATLAB, use the built-in function: lab_image = rgb2lab(rgb_image)
for image conversion, or lab_values = rgb2lab(reshape(rgb_vector, [1, 1, 3]))
for individual RGB values. MATLAB automatically handles the gamma correction, XYZ transformation, and CIELAB calculation using industry-standard formulas and D65 illuminant for accurate color science applications.
LAB color space offers several advantages: (1) Perceptual uniformity - equal distances in LAB correspond to equal perceptual color differences, (2) Device independence - LAB values are consistent across different devices and displays, (3) Better color difference calculations using Delta E formulas, (4) More accurate color interpolation and gradient creation, (5) Scientific color communication standards, and (6) Improved color correction and manipulation algorithms for professional applications.
Yes, RGB to LAB conversion is essential for print design workflows. LAB serves as an intermediate color space for accurate RGB to CMYK conversion, preserving color appearance across different media. The device-independent nature of LAB ensures consistent colors from screen to print, making it ideal for color matching, proof validation, and maintaining color fidelity in professional printing applications with ICC color profiles and color management systems.
RGB to LAB color conversion is a fundamental process in color science, digital imaging, and professional color management. Our RGB to LAB converter calculator provides accurate, standards-compliant conversion using CIE mathematical formulas, supporting Python OpenCV implementation, MATLAB code, Excel functions, and JavaScript applications for comprehensive color space transformation workflows.
The RGB color model (Red, Green, Blue) is an additive color model commonly used in digital displays and computer graphics, while CIELAB (L*a*b*) is a perceptually uniform, device-independent color space designed to approximate human vision. Converting from RGB to LAB using mathematical formulas and equations allows designers, photographers, scientists, and developers to work with color in ways that more closely match human perception and provide cross-device consistency.
Our comprehensive RGB to LAB converter tool provides not only real-time conversion capabilities but also educational resources including step-by-step mathematical formulas, programming code examples in Python (with OpenCV support), MATLAB implementations, Excel spreadsheet functions, and JavaScript code for web applications. This makes it an invaluable resource for color science education, professional color management, computer vision applications, and scientific research requiring precise color space conversions with mathematical accuracy and industry-standard compliance.