In this class we created the categories for our blog posts on our websites. The categories are the learning objectives that are based on the outcomes of the class.
The learning outcomes include:
- 1. Recall the creative process, social environment, and visionaries involved in the journey to the digital world we live in today.
- 2. Clearly explain the essence of what it means to be digital.
- 3. Classify objects or concepts (from 3400 B.C. to modern) as digital or not digital.
- 4. Explain the advantages and limitations of a digital representation in a historical as well as modern context.
- 5. Demonstrate the process of digitization as it applies to text, sound, and images (2D and 3D), including the tradeoffs that must be considered in the process.
- 6. Contrast the digital representation of an object or concept with the “natural” object. What is gained? What is lost?
- 7. Critique the ideas of others with regard to an object, process, or concept of a digital nature. Your critique should incorporate an interdisciplinary perspective gained from other core courses or from your major area of interest.
- 8. Formulate and defend a position on the benefits and liabilities associated with an object, concept, or process that has become digital, relative to its pre-digital existence. Your position must include an interdisciplinary perspective.
- 9. Effectively reflect on and share your experience, what you have learned, in this class, via a webpage and blog. By the end of the course, your blog should address all of the Learning Objectives shown above.
At least one of these categories must be attached to each of our blog posts.
In the digital world, images are represented not as continuous sweeps of paint or shades on paper, but as discrete bits of data. At the heart of this representation is the concept that every image can be broken down into a grid of pixels, each holding color information that can be encoded into binary digits—0s and 1s.
When you take a digital photo, your camera is essentially capturing light through a sensor composed of millions of tiny pixels. Each pixel detects the intensity of light and the colors red, green, and blue—the primary colors of light. The strength of each color at each pixel point is measured and converted into a numerical value. For example, in a 24-bit color system, each color component can range from 0 to 255, encapsulating the intensity of the color. This data is then converted into binary form.
Thus, a single pixel’s color can be represented by a sequence of 24 bits in binary form. For instance, a bright red might be represented as 11111111 00000000 00000000, where each section of eight bits represents the intensity of red, green, and blue, respectively.
The entire image is a compilation of these binary codes for all the pixels arranged in the grid, which your computer or any digital device interprets and reconstructs into the image you see on the screen. The storage size of the image depends on the number of pixels it contains and the bit depth (color information) of each pixel.
Understanding this digital transformation is crucial, especially in fields like graphic design, digital media, and computer programming, where image manipulation and digital image processing are fundamental. By mastering the binary representation of images, professionals can achieve more precise control over image editing, compression, and enhancement, paving the way for innovations in digital imagery.