Creative Workflow in Lightroom

The photographer’s guide to managing, developing, and sharing your work

Jason Bradley

• Publisher: Routledge
• Year: 2016
• Print ISBN: 9780415745024
• eBook ISBN: 9781317755838
• Topic: Media & Performing Arts
• Subtopic: Digital Media

Adobe's Lightroom has emerged as a must-have software due to its powerful editing tools and time saving organizational capabilities but how you establish a personalized, creative workflow that optimizes this technology, your time, and your art eludes most photographers. Jason Bradley, award-winning photographer and Lightroom pro, shares the answers to these questions in this practical and easy to follow guide that taps into the "how" and the "why" of a professional photographer's creative workflow in Lightroom.

Bradley will show you how all workflows can be simplified into three steps: establishing, managing, and rendering the file, alongside stunning photographs and explanations from his own experiences. This book will not only teach you how to work within Lightroom but, ultimately, how to make Lightroom work for you.

Raw File Processing Workflow

Welcome to the fun part! Welcome to the phase of our workflow where we get to lay the groundwork for creating and developing raw files. This is the phase where we start playing with our images, and is where we can plug in the creative side of our brains. And the keyword to use here is play. Regardless of the books you read, or the videos you watch on Lightroom and raw file developing, there is no better teacher than spending time experimenting with your images. Only you have understanding about the vision for your images, can nurture your own sense of design and style, or develop your understanding of when to use one tool vs. the other in the Develop Module. So, learning what tools are in the Develop Module is essential, learning the “tips and tricks” so you too can shoot like a pro, as they say, is important, but most important is for you to figure out how to connect with a vision for your work, and then play, play, play in the Develop Module.

5 The Art of Capture and Process

DOI: 10.4324/9781315798202-5

Image Processing

Developing images is the most personal part of the photographer’s workflow. A hundred photographers could use precisely the same steps for managing their assets, and in doing so there would be no consequence. But this would not be the case with raw file and image development workflow. If everyone developed their images in the same way, photography and craft would quickly become stale and boring. Nevertheless, as important as it is to foster your own style, you first need to become accustomed to the tools at hand. Thus, this section of the book deals with showing you the tools in our creative arsenal.

What Are Raw Files, or RAW Files?

This is probably of little surprise to most of you, but I recommend shooting raw files. They are just a better way to go, and there are many reasons as to why. To help us wrap our heads around why, let’s talk about the format’s spelling because it actually helps us understand what raw or RAW is. I’d say most books, articles, and manuals have adopted the spelling of the file type as “RAW,” and not “raw” today—and this is done to maintain consistency in the world of image formats. JPEG, TIFF, PSD, NEF, CRW, and PNG are all acronyms for image formats and are thus typically capitalized, so raw is usually spelled as RAW. But this implies that RAW is an acronym and a format, which it is not: RAW is an adjective, not a noun. Clarifying this distinction is important because the word raw actually describes the state of the data, much like uncooked food is raw because it has not gone through a processing phase of preparation. It’s true that NEF is the Nikon raw format, CRW is the Canon raw format, and DNG stands for “digital negative,” but these are formats that house raw data and metadata. Shooting raw means you are capturing data that still needs to be processed—or better yet, data that needs to be developed. But to understand how this all works, and how to best take advantage of this technology, we need an understanding of how digital cameras capture light and what it means to “process” a file.

Color Filter Arrays

It’s safe to say that most shutterbugs today know what a pixel is, or at least have a vague idea what one is. In a nutshell, the individual pixel on a camera sensor is a light-sensitive photo diode that reads the amount of light coming into the camera, which is later transposed into data. However, pixels are also blind to color. They only register the amount of light coming in at a particular point, and can’t interpret anything else about it. Therefore a big piece to the image-processing puzzle is to not only read the light but to also translate it, and the first step in that process is the Color Filter Array (CFA). The CFA is placed in front of the camera and is made up of the primary colors—red, green, and blue—which in turn designates a specific color for each individual pixel (see Figure 5.1). Thus, the basic workflow for camera sensors has light first travel through a micro lens to focus the light. Then the light is filtered by the CFA, so it can be gathered by the pixel array and color identified on the individual pixel level.

Like variety in the world of sensors, there’s also variety with CFAs in photography (see Figure 5.2). The vast majority of digital cameras

5.1 Here is a sensor's workflow, so to speak: Light travels through a micro lens to help maximize light capture, it travels though a color filter, and then is captured by a pixel. The light energy is converted into an electrostatic charge, which is then stored as raw unprocessed data

5.2 Color filter arrays assist camera sensors in constructing a color image. The configuration on the left is used by Fuji in a few of its cameras, but the Bayer filter array on the right is used in the vast majority of cameras made and used today

and video cameras use the Bayer filter array developed by Bryce Bayer of Eastman Kodak. The Bayer array was patented in 1976 and is mostly made up of green filters, or as he called them luminance-sensitive elements; the remaining blue and red filters he referred to as chrominance-sensitive elements. The logic behind the Bayer CFA architecture is to mimic the makeup of the human eye, which has more green than red and blue photosensitive cone cells. Specifically, 50% of the pixels on digital sensors are dedicated to green light, 25% to red light, and 25% to blue light. What this means is that individual pixels can grab only the light of a specific color. There are a few variations in CFAs used in digital photography. Sigma, along with many high-end video cameras, actually forgoes the use of color filters by using three sensors, each dedicated to a specific color channel. Fuji is one of the exceptions in still photography, incorporating the X-Trans color filter array into many of its consumer cameras to combat an unwanted artifact in digital image processing called moiré. However, they are a rare exception, as it’s mostly a Bayer CFA world.

Processing Raw Data

Once light has traveled through your camera, passed your CFA, and been captured by the sensor, the raw data is stored. But in order to see a rendering of our raw data, whether it’s on the back of our camera or in Lightroom, the data needs processing. The file needs to go through some intense math to be demosaiced (pronounced deemoe-zay-icked), or interpolated, and have a color profile applied to it. Without such steps the raw data just sits in its unviewable raw state.

CFA demosaicing, or interpolation algorithms, quite literally rebuilds a full-color image from the incomplete raw data. For example, only 25% of my pixels can capture red light, but if I take a picture of, and fill the frame with red balloons as shown in Figure 5.3,

5.3 When photographing a subject that is all red, green and blue light doesn't make its way to the sensors' pixels nearly as much. Because 75% of the sensor is blue or green, those areas need to be interpolated to reconstruct an image with seamless tonality and detail. The word interpolation literally means to introduce something between other things or parts

5.4 Averaging neighboring pixels during processing creates the color of each pixel, and combining red, green, and blue primary colors in different ways can produce any color variation. The color of the pink pixel has a red value of 227, a green value of 110, and a blue value of 225. The blue and the yellow pixels are also combinations of different red, green, and blue values

I can see seamless tonality and detailed edges in my processed image. Since my camera sensor sees the world in mostly blue and green, the missing information needs to be reconstructed or interpolated. There are many kinds of demosaicing algorithms, but the magic of the whole thing is accomplished through the basic idea of being able to obtain any color through a set of primary colors— red, green, and blue (RGB) being our primary set.

Figure 5.4 shows a smattering of differently colored balloons, with a look at pixels within three specific sections of that image. Each pixel is actually a combination of three different values of red, green, and blue. In essence, demosaicing math isolates a cell from the Bayer filter array and analyzes it in different ways and in different directio...

Table of contents

• Cover Page
• Half Title Page
• Frontmatter Page
• Title Page
• Copyright Page
• Table of Contents
• Foreword
• Introduction
• SETTING THE STAGE FOR A LIGHTROOM WORKFLOW
• FILE MANAGEMENT WORKFLOW
• RAW FILE PROCESSING WORKFLOW
• FILE OUTPUT WORKFLOW
• Index