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Quizzes > Computers & IT

Which Statement About Analog and Digital Images Is True?

Quick, free quiz on analog vs digital images. Instant results.

Editorial: Review CompletedCreated By: Paul HomerUpdated Aug 28, 2025
Difficulty: Moderate
2-5mins
Learning OutcomesCheat Sheet
Paper cutout analog waveform beside digital pixel grid, golden yellow background, analog vs digital quiz

This quiz helps you spot the true statement about analog and digital images, including basics like sampling, pixels, and noise. Build quick instincts as you compare examples and get feedback. If you want more challenges, check out the adjustment layers quiz, the multimeter quiz, and a logic check on which statement is true.

Analog images differ from digital images because analog images have:
Binary encoding of color values
Discrete pixel representation
Fixed resolution grid
Continuous tonal variations
Analog images represent information as continuous variations of color and brightness, unlike digital images which use discrete samples. These continuous variations allow for an infinite number of tonal levels. Digital images approximate these tones by sampling and quantizing values.
Digital images are composed of discrete elements called:
Waveform
Bit
Frame
Pixel
A pixel, short for picture element, is the smallest unit of a digital image, representing a single point in the raster grid. Each pixel holds color or intensity information. Grouping pixels together forms the full digital image.
Which of the following is a characteristic of analog film photography?
Infinite tonal gradations
Fixed pixel grid
Limited color space
Discrete sampling
Analog film captures light as a continuous chemical process, producing virtually infinite tonal gradations. This allows subtle transitions in color and brightness without discrete steps. Digital images, by contrast, approximate these tones with finite levels.
Which unit measures the number of distinct brightness levels per pixel in a digital image?
Bit depth
Megapixel count
DPI
Frame rate
Bit depth indicates how many distinct values (levels) each pixel can represent. For example, an 8-bit image can display 256 levels of brightness. Higher bit depths increase color precision and dynamic range.
What is the process of converting a continuous analog signal into discrete digital values called?
Dithering
Interpolation
Multiplexing
Sampling
Sampling is the process of measuring the analog signal at regular intervals to create discrete data points. These samples are then quantized into digital values. Without sampling, a continuous analog signal cannot be digitized.
In digital images, increasing the bit depth increases:
File compression ratio
Resolution in pixels
Dynamic range
Frame rate
Bit depth determines how many tonal levels per channel a pixel can represent, directly affecting the dynamic range - the difference between the darkest and brightest values. More bits allow smoother gradients and reduce banding.
Film grain in analog photography is analogous to which phenomenon in digital images?
Digital noise
Pixelation
Banding
Aliasing
Film grain appears as random speckles on analog film, similar to digital noise which manifests as random variations in pixel brightness or color. Both degrade image quality but originate from different sources.
What phenomenon occurs when the sampling rate is too low for the analog signal in imaging?
Aliasing
Quantization
Dithering
Compression
When sampling below the Nyquist rate, high-frequency details are misrepresented as lower frequencies, causing aliasing artifacts. In images, this appears as moiré patterns or jagged edges. Proper sampling prevents this.
Which file format is typically uncompressed and commonly used for simple digital images?
GIF
PNG
BMP
JPEG
BMP is a simple raster format that stores pixel data without compression, resulting in larger files but exact reproduction of pixels. It's often used in Windows environments.
Which of the following best describes dithering in digital images?
Removing noise from images
Increasing resolution by interpolation
Simulating more colors by mixing pixels
Compressing images losslessly
Dithering adds controlled noise to reduce quantization artifacts, making limited palettes appear smoother by mixing pixel colors. It's widely used in indexed-color images.
Quantization error in digital imaging often leads to:
Increased dynamic range
Color banding
Lower file size
Improved sharpness
Quantization error occurs when continuous values are rounded to discrete levels, causing flat regions or visible steps known as banding. Increasing bit depth or dithering can mitigate this.
Oversampling in digital signal processing can reduce:
Aliasing artifacts
Frame rate
Bit depth requirements
Pixel count
By sampling at rates higher than twice the highest signal frequency, oversampling pushes aliasing artifacts out of the band of interest, which can be filtered out later.
Which image compression method is lossless?
MPEG
JPEG
MP3
PNG
PNG uses lossless compression, preserving all original image data without introducing artifacts. JPEG is lossy and sacrifices some data to reduce file size.
In digital color images, the RGB model uses how many color channels?
1
4
3
2
The RGB color model represents images using three channels - Red, Green, and Blue. Each channel holds intensity values that combine to produce a full-color image.
According to the Nyquist theorem in imaging, the sampling frequency must be at least twice the highest signal frequency to avoid:
Aliasing
Banding
Quantization
Compression artifacts
The Nyquist - Shannon sampling theorem states that to faithfully reconstruct a signal, it must be sampled at least twice its highest frequency component. Sampling below this rate leads to aliasing.
Which technique reduces aliasing by smoothing the signal before sampling?
Low-pass filtering
Edge detection
Histogram equalization
Dithering
A low-pass (anti-aliasing) filter attenuates high-frequency components that cannot be sampled correctly, preventing aliasing artifacts after sampling.
What is the main advantage of vector graphics over raster images?
Infinite scalability without loss of quality
Larger file size
Greater photographic realism
Pixel-based editing
Vector graphics use mathematical paths rather than pixels, allowing them to scale to any size without pixelation or loss of quality. They are ideal for logos and illustrations.
Which type of noise in analog film is characterized by random fluctuations in brightness?
Speckle noise
Film grain
Gaussian noise
Salt-and-pepper noise
Film grain arises from the random distribution of silver halide crystals on film, producing a textured pattern of brightness fluctuations. It's inherent to analog film processes.
What does bit-plane slicing in digital images allow you to do?
Convert analog signals
Compress image with loss
Combine multiple images into one
Enhance specific bits of pixel values separately
Bit-plane slicing separates an image into its individual bit-level layers, enabling analysis or enhancement of particular significance levels. It's useful for feature extraction.
Which of these is a primary advantage of CCD sensors over CMOS in digital cameras?
Faster readout speed
On-chip integration
Lower power consumption
Lower noise and higher image quality
Charge-coupled device (CCD) sensors historically offered lower noise and higher image uniformity compared to early CMOS sensors, making them popular in high-end imaging.
Which statement about RAW image files compared to JPEG is true?
RAW files contain unprocessed sensor data
RAW files are compressed with lossy algorithms
RAW files use 8-bit color depth
RAW files have smaller file sizes
RAW files store the unprocessed data directly from the camera sensor, preserving maximum detail and bit depth. JPEG applies in-camera processing and lossy compression.
Which anti-aliasing method in digital imaging uses multiple samples per pixel and averages them?
Post-filtering
Multisampling
Supersampling
Edge smoothing
Supersampling anti-aliasing (SSAA) renders the image at higher resolution and then downsamples by averaging multiple samples per pixel, effectively reducing aliasing.
In digital image interpolation, using a finite impulse response (FIR) kernel instead of an ideal sinc function typically results in:
Perfect reconstruction without artifacts
Infinite computation time
Increased aliasing artifacts
Reduced ringing but slight smoothing
Finite FIR kernels approximate the ideal sinc interpolation, reducing computational cost and ringing artifacts but introducing a small amount of smoothing. They balance quality and efficiency.
Which adaptive sampling technique in digital imaging adjusts sampling density based on image content to optimize quality?
Random sampling
Nyquist sampling
Adaptive sampling
Uniform sampling
Adaptive sampling increases sample density in areas of high detail or contrast while reducing it in simpler regions, optimizing resource usage and preserving image quality.
What is the principle behind sigma-delta analog-to-digital converters used in high-end digital imaging?
Lossy compression during conversion
Oversampling combined with noise shaping
Direct quantization at Nyquist rate
Single-bit sampling without filtering
Sigma-delta ADCs oversample the input signal at a much higher rate and shape quantization noise out of the band of interest, achieving high resolution after digital filtering.
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Study Outcomes

  1. Understand analog vs digital signals -

    Gain a clear grasp of continuous waveforms and binary representations that distinguish analog vs digital signals.

  2. Differentiate analog and digital images -

    Recognize the key differences between continuous-tone analog images and discrete-pixel digital images in terms of data format and resolution.

  3. Analyze data conversion processes -

    Explore how sampling, quantization, and encoding transform analog signals into digital formats and vice versa.

  4. Identify the true statement about analog and digital images -

    Apply your knowledge to determine which statement accurately reflects the properties of analog and digital images.

  5. Apply quiz insights -

    Test your understanding in a scored environment to reinforce concepts and measure your mastery of analog vs digital formats.

Cheat Sheet

  1. Continuous vs Discrete Signals -

    Analog images capture continuous changes in light intensity, forming an uninterrupted waveform, while digital images encode information into discrete binary pixels. As highlighted by MIT OpenCourseWare, this continuity vs. discreteness is the cornerstone of analog vs digital signals. Mnemonic: "Analog all the way, digital bits at play."

  2. Sampling Theorem & Quantization -

    Sampling and quantization convert analog waveforms into digital data by measuring signal amplitude at regular intervals (fs ≥ 2 fm, per the Nyquist theorem). For example, audio sampling at 44.1 kHz ensures fidelity up to 20 kHz, a principle you'll see in digital imaging's pixel quantization. Think "Double your rate to avoid aliasing" when considering analog vs digital image sampling.

  3. Resolution, Bit Depth & Dynamic Range -

    Analog images offer theoretically infinite resolution and smooth tonal transitions, whereas digital images are defined by a fixed pixel grid and bit depth (e.g., 8-bit vs. 12-bit raw files). According to IEEE standards, higher bit depths increase dynamic range and color precision in digital vs analog images. Remember: more bits, more brilliance!

  4. Noise Immunity & Signal Integrity -

    Analog systems accumulate noise and distortion as signals propagate, but digital formats leverage error correction and regeneration to maintain signal integrity. The ITU and IEEE note that digital transmissions can use CRC or checksums to detect and correct errors, giving digital vs analog signals a clear advantage. A handy tip: "Digital defies noise" to recall why digital shines in long-distance transmission.

  5. True Statement: Continuity vs. Pixels -

    In response to "which statement about analog and digital images is true?", recall that analog images vary continuously in tone, while digital images are composed of discrete pixels and binary values. As you test yourself in this analog vs digital quiz, remember that difference between analog and digital images revolves around continuity versus sampling. Keep this fact at hand: "Continuous curves vs. counted cubes."

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