Pixels & Resolution:

Project Description

Pixels & Resolution

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Digital Image Sensor

Sensor Comparison


1 Megapixel = 1,000,000 pixels or a 1,000 x 1,000 pixel image.

Megapixels Common Print Size
2MP 6×4″
3MP 7×5″
4MP 8×6″
6MP 10×7″
8MP 14×10″
12MP 24×16″

From the table above it should be clear that most of us hardly need more than 6.0 megapixel from our pocket cameras. So don’t get carried away by the megapixel count when buying a digital camera. If you really need bigger prints, then you should look at professional SLR cameras or semi-professional cameras with large sensors to meet your megapixel needs. A camera will a small sensor boasting a lot of megapixels will probably disappoint you in the long run.

Image result for pixel resolution photography comparison

Compression Vs Resolution

Image result for compression pixels comparison

Higher resolution or lower compression JPG’s?

The question often arises as to whether to choose high resolution at high compression or low resolution at low compression, if both result in the same file size. As a test, I have chosen an image that has proven to be challenging for JPG so that we can see the limits of JPG compression. Below are two versions of the image at resolutions differing by a factor of two:

High resolution
file size = 70,106 bytes

Low resolution
file size = 17502 bytes

Following are JPG’s of the same two images, with compression chosen to yield approximately the same file size for each:

High resolution
File size = 3,984 bytes

Low resolution
File size = 4,068 bytes

Now let’s magnify these images to make the differences easier to see.

High resolution
Image magnified x 2

Low resolution
JPG file size = 4,068
Image magnified x 4

To my eye, the first image is clearly superior. Pixelation is much less noticeable, and the color degradation resulting from the JPG chroma subsampling is much, much less severe. The stripes are red, as they should be, rather than the purple we see on the right.

Some have suggested that a fairer comparison for viewing might be to do a bicubic resizing of the small image to match the dimensions of the larger image. Here is the result:

High resolution
JPG File size = 3,984 bytes

Low resolution
JPG file size = 4,068 bytes, then bicubic resized x 2.

and magnified x 2:

High resolution
JPG File size = 3,984
Image magnified x 2

Low resolution
JPG file size = 4,068, then bicubic resampled x 2.
Image magnified x 2.

The pixelation disappears if bicubic resizing is gone, but the image at right is clearly not nearly as detailed as the image at left. The red stripes are still purple, of course.

Pixels and Resolution

Digital Photography is a form of photography that uses an array of light sensitive sensors to capture the image focused by the lens, as opposed to an exposure on light sensitive film. The captured image is then stored as a digital file ready for digital processing (colour correction, sizing, cropping, etc.), viewing or printing.


Resolution can be defined as the total number of pixels in a binary (digital) or bitmap image (an image made up of pixels). So a high-resolution image has more pixels than a low-resolution image. The higher the resolution, the more pixels you have to play with, but also the larger the file size.

Digital images are normally rectangular in size and shape, that way we can determine the pixel dimensions easily. The proper way to list the pixel dimensions of an image is [WIDTH] x [HEIGHT]. This will also determine the orientation of an image. An image that is wider than it is tall is a landscape (or horizontal) orientation. If the image is taller than it is wide, it is a portrait (or vertical) orientation. So an image that is 400×300 pixels is a landscape orientation, since the first number (width) is larger than the second number (height). Therefore, an image that is 400×600 pixels is… portrait orientation. Get it?

Portrait Orientation Landscape Orientation
This image is 200×300 pixels This image is 300×200 pixels


Pixel Resolution is measured in Pixels Per Inch (PPI), an easy way to gauge the resolution of an image.

Normal Screen Resolution (72ppi) Low Resolution (10ppi)

When the image has a low enough resolution that the pixels are visible to the eye, then it becomes pixelated. Or when you take a low resolution image and enlarge it to a much bigger size, the smaller pixels expand and you will see the pixelization. Changing the PPI of an image requires fitting the image into a different resolution, therefore modifying the pixel structure. This is called interpolation, when you squeeze or stretch pixels into another resolution.


In step 6 (resize) above, you will be resizing your high-resolution image (6MP or more) for the computer screen ( less than 1MP). This process of fitting your high-resolution image into a lower-resolution image is called INTERPOLATION. The target resolution for a computer screen is 72ppi. A computer screen doesn’t need as much resolution to present your image since most computer screens are 2 megapixels or less. This way we can get away with using a much smaller, low resolution image file. For example, the HD or high-definition screens that are becoming so popular these days are only 2,000,000 pixels (or 2MP) or less. Several years ago, the largest computer screen was 640×480 pixels (or 307,200 pixels – less than a third of a megapixel).

Let’s look at how interpolation works:

Reducing or Decreasing the Size/Resolution (Losing Pixels)

When you reduce a high-resolution image for use on a computer screen, you are essentially squeezing your image down into a smaller resolution. Those MILLIONS of pixels will have to be condensed into the smaller resolution, averaging out the color and tones of groups of pixels and making them one. Notice there are a group of four pixels on the left for each one pixel on the right. You are distributing the pixels of the image into less pixels than the original version.

Enlarging or Increasing the Size/Resolution (Gaining Pixels)

When you enlarge a low resolution image, it stretches out the pixels, then fills in the empty pixels with an average of the neighboring pixels. This can degrade an image and make it blurry or pixelated, depending on how the image is interpolated.



There are two types of image files that a digital camera can produce: RAW and JPG (and sometimes TIFF). Let’s take a look at this chart:

Ready for Editing Already Edited

RAW file is delivered with every single pixel untouched, just as the camera captured it. A JPG file, however, is manipulated by the camera which messes around and compresses pixels before it delivers it to you.

Now, the baked apple pie looks more appealing, doesn’t it? Maybe to a non-baker, but usually a baker would want to purchase apples and make their own pie so they could control the seasoning, cutting and baking the pie to be just the way they want. That’s how a photographer looks at their digital images. They want the APPLE so they could make their own PIE. They don’t want the camera messing around with the pixels and making decisions for them so they could “chop, season and bake” their own image just how they want.

So how does compression work?

Compression happens when you save an image and set the quality setting (or when the camera saves your JPG image to your SD memory card). The image processor looks for adjacent TWINS in the image. Twin pixels that is, as many as it can find that are the same. It will count those pixels that are exactly the same only once and store that pixel data only once so it will have a smaller file size.

Like this:

It doesn’t change the size of the pixels, but finds the same adjacent ones and saves the data only once for that range of pixels.

So, for a JPG with LOW COMPRESSION (high quality), these identical twin people (pixels):

are all counted and shown as:

thus making a smaller file size because it’s not counting every pixel, but grouping them and counting them only once.

Ok, so what happens when you compress at a higher rate?

Compression at a higher rate starts to look at SIMILAR pixels, not EXACT TWIN pixels. Therefore, the more you compress, the less exactness it finds. So for example, a JPG with HIGH COMPRESSION (low quality), these marginally SIMILAR people (pixels):

are all counted and shown as:

thus making a much smaller file size because more pixels are grouped up and are counted as one.

The outcome?

Compression is especially hard on detail and edges within your image. Your photos will lose detail, become mottled, and you’ll see banding of pixels:

Low Compression (20%)
High Compression (100%)
  • Notice the smooth tones
    in the sky and wood planks.
  • Only very close matches
    were counted as one.
  • Notice the banding and
    mottling of pixels.
  • Somewhat similar pixels were
    counted as one.

This is known as ARTIFACTING.



Any kind of compression in a JPEG file does basically the same thing. It looks at the adjacent pixels, and if it’s within a certain threshold, it will change the adjacent pixel or pixel group to be a similar colour as itself. So if you have a big single colour area, then it saves the colour, and the start and end point of the line on the same colour, instead of saving the details on every pixel in the line. When this is visible, by mottling or banding in the image, it is known as Artifacting.

How does it differ from Pixelization?

Let’s look at the difference between artifacting and pixelization.

Low Resolution Image (10ppi)
Highly Compressed Image (72ppi)
Pixelization happens when the pixels are visible to the eye due to a low resolution (pixels per inch) that has been enlarged.This is caused by:
Interpolation of Pixels when Resizing.
Artifacting occurs when an image is compressed so much that the banding of pixels together is visible in the image.This is caused by:
Compression of an Image when Saving



When you crop an image, you are deleting pixels. Plain and simple. Here’s an example:

Original Image Cropped Image

Once you delete those pixels, they are GONE. You have also created an image with less pixels, so it is a smaller resolution to work with. That is another reason to use the highest setting on your camera to capture the most pixels possible. That way you will have room to crop when needed.


Maintain your Original!

As you can see, cropping, resizing (interpolating) or changing the image quality (compressing) will mess with your pixels. And the more you do it or redo it, the more pixels change from your original. And every time you save and resave  a JPG file, it recompresses it. That’s why it is best to keep your original intact and do a save as every time you resize, crop or otherwise change your image. You can have many versions of the same photo rendered out from the original file. You can have a high-resolution version, a low resolution version, a black and white version, a color version, a toned version, an internet version, a print version, an 8×10 version, a 16×20 version, etc.

So ALWAYS start from your original and output your final image (save as) for its intended purpose (web, large print, small print, color print, B&W print, etc).

Project Details

  • Date November 1, 2016
  • Tags BDP, BDP Lessons

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