AI and the Color Imaging Revolution

Understanding the role of artificial intelligence in Hikvision's ColorVu technology

AI is revolutionizing video security, contributing significantly to advancements in object recognition, search capabilities and real-time threat detection. However, AI's impact extends beyond these areas, particularly in enhancing the quality of video images. Cutting-edge AI, powered by advanced chipsets and AI-driven technologies, is overcoming traditional challenges in image quality, particularly in ultra-low light conditions. The result is precise color rendering and razor-sharp, clear images that were previously unattainable.

Challenges of low light in video cameras

Historically, video cameras faced multiple challenges in low-light environments. Cameras struggled to capture sufficient light, leading to electronic signal boosting, which introduced unwanted "grain" or "noise" into the video. Slow shutter speeds, necessary for letting in more light, caused blurry images when there was any movement. Autofocus does not work well in low light due to insufficient contrast and lack of a clear focal point. Additionally, colors were not accurately reproduced, and artificial lighting could distort natural hues. Shadows and deep contrasts further obscured important details, lowering the dynamic range.

However, the integration of AI into image processing has significantly elevated video quality. AI-empowered ISPs now simulate human vision by performing real-time adjustments for auto-focusing, exposure control, and white balance. The technology reduces noise and improves clarity and detail, making images more closely resemble what we see with our eyes. AI adjusts camera settings dynamically based on lighting and scene changes, ensuring consistent image quality across various environments.

Edge technology manufacturers like Hikvision seeking to achieve these AI-driven advancements in image quality must become proficient in several critical steps:

• First, AI integration requires comprehensive data collection and preparation. Diverse image samples are gathered and accurately labeled to create a robust dataset.
• Second, careful attention must be paid to AI model selection and training. The appropriate algorithm is selected, and AI models are trained to enhance image quality using the prepared data.
• Next, a disciplined approach to testing and optimization must be thoroughly developed. The model's performance is rigorously evaluated, and necessary adjustments are made to optimize results.
• Lastly, deployment is followed by continuous improvement. Once integrated into real-world applications, the AI model is continuously refined based on new data and user feedback.

How hardware components enable AI signal processing

There are four critical hardware components that enable AI-driven enhancements in video imaging:

Image Sensors: Larger and more sensitive CMOS sensors capture more light, significantly improving image quality in low-light conditions. These sensors provide a solid foundation for AI processing.

Image Signal Processor (ISP): The ISP handles noise reduction, white balance, contrast adjustment and color correction. With AI acceleration, the AI-ISP runs complex image processing algorithms faster and more efficiently.

AI-Enabled System on Chip (SoC): The SoC supports deep learning algorithms, providing the computational power necessary for real-time image recognition, classification, and enhancement.

Memory: Upgraded high-speed, high-bandwidth memory ensures that the processor can quickly handle large amounts of data, facilitating smoother and faster AI-driven image processing.

How Hikvision uses AI to enhance video imaging

Several AI trends are making this technology increasingly desirable for enhancing video image quality.

Fundamentally, AI enhances the perceptual capability of hardware by adjusting image parameters automatically, providing optimal image quality even in low-light conditions. A benefit of the rise in high-performance processors is the streamlining of powerful but costly SoCs, enabling cost-efficient, high-quality image processing with low power consumption.

Another key trend is multimodal fusion, or the process by which AI integrates data from multiple sensors, such as visible light, audio and infrared, to create more accurate and comprehensive images, further improving image quality.

Hikvision's ColorVu technology leverages AI to deliver high-quality, full-color video in low-light conditions. Let's explore how AI significantly enhances various aspects of video imaging in Hikvision's ColorVu products.

AI-enabled 3D LUT Color Correction employs a full 3D color space to control image parameters such as color, brightness and saturation. This precise color calibration results in more accurate and vibrant images in practical applications.

Noise reduction is maximized through AI analytics. By analyzing vast amounts of data from low-light scenes, AI constructs intelligent noise reduction algorithms that effectively distinguish between useful signals and noise, filtering out the latter to enhance image purity.

Motion blur reduction is accomplished when AI uses smart algorithms within the SoC to address motion blur in low-light environments, resulting in clearer and sharper images even when there is movement.

The benefits of enhanced Wide Dynamic Range (WDR) are realized when AI combines multiple image exposures through intelligent algorithms to significantly boost dynamic range. This ensures that bright areas are not overexposed, and details in dark areas are preserved, creating a balanced and natural-looking image.

Lastly, AI enables intelligent object recognition to enhance the clarity of important targets, such as vehicles and license plates, making these elements more distinguishable when using ColorVu products.

What's ahead: The next wave of innovation

Real-Time High-Definition Enhancement: AI will use super-resolution technology to upscale low-resolution video to high definition in real-time, allowing even cameras with lower resolutions or those capturing footage from long distances to provide clear, detailed images.

Multi-Camera Collaboration: AI will enable coordinated operation among multiple cameras, ensuring seamless tracking of moving objects across different viewpoints. This technology will stitch together perspectives from various cameras to create comprehensive panoramic images, providing a more complete view of video security.

Multi-Perception Fusion: AI will integrate data from various sensors, such as visible light, audio, X-rays, infrared and radar, to perform multi-perception fusion processing. This approach enhances overall image quality and perceptual effects, making video imaging more robust and informative.

Research and development drive the next evolution

Hikvision remains at the forefront of AI-driven video imaging, pioneering advancements in low-light conditions with our industry-leading ColorVu technology. They invest heavily in research and development to advance core technologies such as multi-dimensional perception, AI and big data, setting the standard for color IPC performance in challenging lighting environments.

Hikvision is at the forefront of AI-driven innovation, redefining video imaging, especially in low-light scenarios where we continue to push the boundaries of what's possible. This advanced technology is integrated across their comprehensive range of security solutions, including IP cameras in various form factors such as panoramic, PTZ, dome, bullet, turret, Analog, solar-powered and Professional VMS. As AI technology evolves, Hikvision remains poised to deliver even greater breakthroughs, enhancing their access control offerings. By continuously advancing AI, Hikvision solidifies their leadership in video security and image quality, ensuring their solutions meet the demands of modern security challenges.