infinity-project.org Engineering education for today’s classroom Outline Images Then and Now Digitizing Images Design Choices in Digital Images Better Design Through the Bit Budget

infinity-project.org Engineering education for today’s classroom Engineering Design Problem Build a system that opens the door to your room for only a few select people How do artificial imaging systems represent visual information?

infinity-project.org Engineering education for today’s classroom 3.1 Introduction

infinity-project.org Engineering education for today’s classroom Images Throughout History From cave dwellers to today, images have played an important role Did you know? About half of our brain activity is image processing Modern engineers have led a revolution in imaging…

infinity-project.org Engineering education for today’s classroom Images Today Increasingly, we are taking images of things that we cannot or will never be able to see We make critical decisions and discoveries using images. As such, The science and math behind images and imagere presentation have never been more important

infinity-project.org Engineering education for today’s classroom Representing Digital Images The smallest feature in a digital image is a “picture element” or pixel. Every pixel has a numerical value - an array of numbers For black-and-white images, the pixel value corresponds to a “shade of gray”. For color images, the pixel value corresponds to a particular color. Each value is stored in binary form. Why?

infinity-project.org Engineering education for today’s classroom Digital Images Can Be Manipulated Crop and Zoom Enhancement, Special Effects Changing images is easy when they are just numbers….

infinity-project.org Engineering education for today’s classroom Movie Magic Movies are sequences of images (frames) that change little by little If the number of frames per second is fast enough, the motion looks continuous!

infinity-project.org Engineering education for today’s classroom Image Recognition System

infinity-project.org Engineering education for today’s classroom Basic Digital Imaging Systems All digital imaging systems have a common block diagram Q: Why is the bird reversed in the display?

infinity-project.org Engineering education for today’s classroom 3.2 Digitizing Images

infinity-project.org Engineering education for today’s classroom Design of Digital Imaging Systems Size of Pixel? Size of Grid? Number of Gray Levels? Color Representation? Frame Rate? These choices determine Resolution Image size for storage Quality Accuracy Enjoyment

infinity-project.org Engineering education for today’s classroom Image Quantization Number of gray values M Number of bits per pixel m Relationship: M = 2 m or m = log 2 (M) 1 bit2 levels 2 bits4 levels 8 bits256 levels

infinity-project.org Engineering education for today’s classroom Design of Image Quantization Fewer bits per pixel means a loss in detail… but fewer bits to store A tradeoff of quality vs. convenience 4 bits per pixel2 bits per pixel

infinity-project.org Engineering education for today’s classroom Problem: Image Quality How many additional bits per pixel does it take to double the image quality (i.e. the number of gray levels)? Answer: One additional bit - which is usually a small increase. For example, going from 6 bits per pixel to 7 bits per pixel increases the gray levels from 64 to 128 and only increases storage by 16.7%.

infinity-project.org Engineering education for today’s classroom Sampling for Digital Images Sampling: Taking measurements at regularly- spaced intervals Sampling Rate: The number of pixels measured over a linear distance. Sampling more often can produce finer details in a digital image, but it requires more effort and storage. Sampling less often can lead to artifacts - another tradeoff.

infinity-project.org Engineering education for today’s classroom Sampling Artifacts: Aliasing

infinity-project.org Engineering education for today’s classroom Temporal Sampling Artifacts in Movies: Wagon Wheel Effect The Blue Wagon’s wheels are rotating backwards! time

infinity-project.org Engineering education for today’s classroom Problems

infinity-project.org Engineering education for today’s classroom Number of Bits Per Image Suppose I = number of pixel rows J = number of pixel columns M = number of gray values per pixel Size of Image in Bits: b = I J log 2 (M)

infinity-project.org Engineering education for today’s classroom Representing Color Images Color images can be represented using red, green, and blue light Color = 3 images, 3 times the storage

infinity-project.org Engineering education for today’s classroom Example Problem: Color Images

infinity-project.org Engineering education for today’s classroom Infinity Project Experiment - 3.1

infinity-project.org Engineering education for today’s classroom Infinity Project Experiment 3.2

infinity-project.org Engineering education for today’s classroom Infinity Project Experiment – 3.4

infinity-project.org Engineering education for today’s classroom 3.3 Putting It Together

infinity-project.org Engineering education for today’s classroom Bits, Bytes, and Storing Images 1 byte = 8 bits Number of bytes/image: B = I J log 2 (M) / 8 Note: 640 x 480 is standard television resolution

infinity-project.org Engineering education for today’s classroom Allocating the Bit Budget If we have a fixed number of bytes to store an image, which is better: more gray levels and fewer pixels, or more pixels and fewer gray levels? The answer depends on many factors: Image content How far away our viewing distance is Our use of the image

infinity-project.org Engineering education for today’s classroom Reducing the Bits Per Pixel 4 bits/pixel (211 kB) 2 bits/pixel (106 kB) 3 bits/pixel (158 kB) 1 bit/pixel (53 kB)

infinity-project.org Engineering education for today’s classroom Reducing the Number of Pixels 163 x 163 (13.3 kB) 82 x 82 (3.36 kB) 41 x 41 (841 bytes) 650 x 650 (211 kB)

infinity-project.org Engineering education for today’s classroom Color vs. Grayscale Images 12-bit color (634 kB) 8-bit color (423 kB) 8-bit grayscale (423 kB) 24-bit color (1.27 MB)

infinity-project.org Engineering education for today’s classroom Taking Digital Pictures Resolution depends on Field of View: area of scene captured Number of pixels in image sensor Using geometric relationships, the effective pixel size is found.

infinity-project.org Engineering education for today’s classroom Calculating Pixel Size Formula: Pixel Size = (Field of View) / (number of pixels) Example: Portrait Field of view = 1.5 m Pixels per row or column = 1500 Pixel size = 1 mm Example: Satellite Photo Field of view = 6 km Pixels per row or column = 4000 Pixel size = 1.5 m

infinity-project.org Engineering education for today’s classroom Capturing Events

infinity-project.org Engineering education for today’s classroom Infinity Project Experiment – 3.5

infinity-project.org Engineering education for today’s classroom 3.4 Better Design within the Bit Budget

infinity-project.org Engineering education for today’s classroom Additional Topics Halftoning - Newspaper Print Color Palettes

infinity-project.org Engineering education for today’s classroom Master Design Problem

infinity-project.org Engineering education for today’s classroom Master Design Problem Design an image and video system for digitally-recording live events Sporting events Theater performances Has this been done? What are the goals and constraints? Movement, Resolution, Image Quality, Portability, Ease of Use

infinity-project.org Engineering education for today’s classroom Master Design Problem (cont.) Research and Gather Information How are live events produced for TV? Create Potential Designs Sketch layout of camera configuration Analyze Designs Calculate field of view, pixel size, number of pixels, storage requirements Choose, Build, Test, Repeat

infinity-project.org Engineering education for today’s classroom End of Chapter 3