OV5642 Weird Colors

1

1716931479732

  1. Where did you get the camera module(s)?

UCTronics

  1. Model number of the product(s).

B0020

  1. What hardware/platform were you working on?

Custom STM32-based board

  1. Instructions you have followed. (link/manual/etc.)

Arducam OV5642 Driver

  1. Problems you were having.

Images are strangely colored.

  1. The dmesg log from your hardware.

N/A

  1. Troubleshooting attempts you’ve made.

Changing XCLK speed from 24MHz to 12MHz, adjusting various settings.

  1. What help do you need?

Any ideas of what to check that could be causing this kind of weird coloring?

2

Hi @gdb3-ampaworks ,
From ChatGPT：
If the lower 8 bits of one pixel are combined with the upper 8 bits of the next pixel, the image data will become corrupted, resulting in significant visual artifacts. Here are the potential issues and the solution:

Potential Issues:

  1. Color/Gray Scale Distortion: Each pixel’s accurate color or grayscale value will be lost. The resulting pixel values will be incorrect, leading to random and unpredictable colors or shades.

  2. Image Artifacts: There will be noticeable artifacts such as stripes, bands, or spots across the image due to the incorrect combination of pixel data.

  3. Loss of Image Detail: The image will lose its original details, becoming blurry or distorted, as the correct pixel information is no longer preserved.

  4. Overall Visual Degradation: The image will appear visually corrupted with unnatural patterns and noise, making it unusable for any meaningful analysis or display.

Example:

Consider two pixels in a 16-bit image (for simplicity, let’s use hexadecimal notation):

Pixel 1: 0xABCD
Pixel 2: 0x1234

If the lower 8 bits of Pixel 1 (0xCD) are combined with the upper 8 bits of Pixel 2 (0x12), the new pixels might look like this:

New Pixel 1: 0xAB12  (Upper 8 bits of Pixel 1 and Upper 8 bits of Pixel 2)
New Pixel 2: 0xCD34  (Lower 8 bits of Pixel 1 and Lower 8 bits of Pixel 2)

This results in completely incorrect pixel values.

Solution:

To solve this issue, you need to ensure that each pixel’s data is correctly read and preserved. This typically involves:

  1. Correct Data Handling: Ensure that the data reading and handling process correctly separates and combines the upper and lower bits of each pixel.

  2. Proper Buffer Management: Use proper buffering techniques to maintain the integrity of each pixel’s data. Make sure that when reading from a data stream, the bytes are correctly aligned and combined.

  3. Data Verification: Implement checks and verifications during the data reading process to ensure that the pixels are correctly formed. This can involve checking for expected byte patterns or using error detection mechanisms.

  4. Use of Libraries or APIs: Utilize established libraries or APIs for image processing that handle the byte alignment and pixel data management internally, reducing the risk of such errors.