CMOS Sensor Noise: Understanding Dynamics & How To Remove It?

Capturing the perfect shot in the world of digital photography often feels like a blend of science and creativity. No matter how good a picture looks, there is an invisible challenge called the CMOS sensor noise. While you might think of it as a human error, this grain is a visual of light interacting with silicon-based image sensors.

If your images have this noise, it will appear as grains, colors, or blur in low light or high ISO settings. Although this can be a real problem for the photographer, there are many effective techniques to make this grain go away. The article below looks into the causes of this noise and how to get rid of it.

Part 1. Types of CMOS Image Sensor Noise

If you want to learn the concept of this noise, you will have to explore its types and their causes. The table below looks into the types of CMOS image sensor noise and discusses all the relevant information:

Photographers often confuse CMOS with CCD noise, which may hinder the noise reduction process. Check out the following points to easily differentiate between the two:

1. Readout Method and Noise Distribution: In CMOS, each pixel has its own amplifier and readout circuitry, whereas the read noise varies across pixels. However, in CCD, pixels transfer charge to a single output amplifier with more uniform read noise but slower readout.

2. Read Noise Level: Although modern CMOS sensors have significantly improved, the previous ones had higher read noise. In contrast, CCDs are ideal for scientific and low-light applications because of their low read noise.

3. Thermal Noise: The noise in CMOS sensors is prone to thermal noise in long exposures. In comparison, the other type of noise is also impacted but controlled due to more uniform charge handling.

Part 2. CMOS vs CCD Noise Comparison

Although the above section comprehensively discusses the comparison between the two types of artifacts, explore the table below for a brief look:

Part 3. CMOS Sensor Low-Light Performance

Now that we have a clear differentiation between the two types of noise, let’s dig deeper into the concept of CMOS and the CMOS sensor low-light performance:

1. CMOS Sensor and its Performance in Low-Light Conditions

In low-light conditions, CMOS sensors increase the noise visibility due to their struggle to collect photons. Cameras often increase the ISO setting as a compensation, which amplifies both the signal and the noise. This leads to grains as random and thermal noise become more prominent.

2. Role of Pixel Architecture and Back-Side Illumination

The structure of each pixel plays an important role in how well it captures light. Traditional front-side illuminated sensors suffer from reduced efficiency due to metal wiring blocking some of the incoming light. Back-side illumination technology flips the structure so light hits the photodiode directly to increase sensitivity.

3. Managing CMOS Sensor Noise in Nighttime

To reduce noise in night scenes, CMOS sensor noise uses both hardware and software techniques. You can use long exposure noise reduction and dark frame subtraction to minimize the grain. If your camera does not have in-camera noise filtering options, benefit from third-party noise reduction tools.

Part 4. CMOS Sensor Noise Reduction Techniques

To refine your image quality, you must understand the intricacies of CMOS sensor noise correction. Look into the following section and gain clarity on the two techniques of noise reduction:

Hardware-Based Noise Reduction

These techniques are built directly into the sensor or the camera hardware to minimize noise at the source. The following points will explain the hardware-based noise reduction techniques in a better way:

1. To subtract out consistent noise, the Correlated Double Sampling captures the before and after light exposure signals.

2. The Analog Gain Control carefully adjusts the amplification of the signal to avoid boosting noise along with the image data.

3. Enlarging the pixels is a good idea, as bigger sizes can collect more light to improve the signal-to-noise ratio in low light.

4. Design enhancements like electrical shielding minimize interference between pixels and circuits.

Software-Based Noise Reduction

Either in-camera or during editing, these techniques are applied after the image is captured to clean up visible noise. You can explore the explanation below and learn the details on this CMOS image sensor noise reduction technique:

1. Use the in-camera noise reduction techniques to smooth out the areas with high noise while preserving the details of the image.

2. With Multi-Frame Stacking, you can capture multiple exposures and merge them to average out random noise.

3. Luminance vs Chrominance Filtering separates brightness noise from color noise and treats them differently to avoid detail loss.

4. If the above-mentioned techniques do not work, you can always invest in a CMOS sensor noise reduction software.

Part 5. Post-Processing CMOS Sensor Noise Reduction From Images: FotorPea

Despite all the efforts made for the perfect photo, imagine sharing a grainy image for your photography thesis. Besides resulting in bad grades, this picture will kill your opportunities as a photographer. If we told you that this artifact can go away by using a robust image enhancer, none of the above situations will happen. With HitPaw FotorPea, you can upgrade your image quality through effective CMOS sensor noise correction.

Besides its conventional noise reduction model, the newly introduced Realistic Denoise model helps you with image enhancement by offering extensive noise removal. This model retains the image details while retaining the original textures. If your image is a combination of blur and noise, the Creative Denoise model will detect the flaws in your picture and fix them with a single click.

Key Features of HitPaw FotorPea

1. Batch Processing: If you have multiple images with CMOS image sensor noise, use the batch enhancement feature to improve their quality.

2. Export Settings: Before you save the enhanced image, you can select the desired image quality and format to get personally tailored outcomes.

3. Preview Results: To be sure of the quality of noise reduction, preview the before and after enhancement results.

A Quick Overview of Using FotorPea to Remove CMOS Sensor Noise

As mentioned above, the picture enhancement process at HitPaw FotorPea is simple and relies just on a single click. The following guide covers a complete guide on using this tool for CMOS sensor noise reduction:

To begin with, open the HitPaw FotorPea’s main interface and use the “Enhance Photos Now” button to head to a new screen.

Using the next screen, select the “+” button at the center and choose the noisy images from your device for quality upgrade.

Once the imported image appears on the screen, select the “Realistic Denoise” model from the “Denoise Model” section. Now, click the “Preview” button and wait for the enhanced picture to be unveiled.

If the enhanced image satisfies you, select the “Export” button at the bottom right to save the picture to your PC.

Conclusion

In summary, this article covered all the details you might need to know about the CMOS sensor noise. While we discussed various techniques to prevent and reduce this artifact, we came across HitPaw FotorPea. This platform is a robust image enhancer that offers numerous noise reduction models to enhance your photography.