Enhanced Layered Image Pickup Device with Adaptive Signal Processing

Publication ID: 26-US12166060B2_0001_PTD
Published: January 16, 2026
Category:Direct Improvements & Enhancements

Legal Citation

pr1or.art Inc., “Enhanced Layered Image Pickup Device with Adaptive Signal Processing,” Published Technical Disclosure No. 26-US12166060B2_0001_PTD, Published January 16, 2026, available at https://archive.pr1or.art/26-US12166060B2_0001_PTD
This technical disclosure describes improvements that would be readily apparent to a Person Having Ordinary Skill In The Art (PHOSITA) when considered in combination with the foundational architecture disclosed in U.S. Patent No. 121,660,602.

Summary of the Inventive Concept

An improved layered image pickup device featuring adaptive signal processing to optimize image quality, reduce noise, and enhance device efficiency

Background and Problem Solved

The original layered image pickup device, as described in the source patent, enables downsizing of device size while maintaining signal processing capability. However, it may still suffer from image quality degradation due to noise and limited processing power. The Enhanced Layered Image Pickup Device with Adaptive Signal Processing solves this problem by incorporating an adaptive noise reduction module, utilizing machine learning algorithms to optimize signal gain and offset in real-time, resulting in improved image quality and reduced noise.

Detailed Description of the Inventive Concept

The Enhanced Layered Image Pickup Device with Adaptive Signal Processing comprises a first structural body and a second structural body layered on top of each other. The first structural body includes a pixel array unit with 1280x720 photodiodes, each measuring 5.5μm x 5.5μm. The second structural body includes an input/output circuit unit, a signal processing circuit, and an adaptive noise reduction module. The adaptive noise reduction module utilizes a machine learning algorithm to analyze image data and adjust signal gain and offset in real-time, resulting in improved image quality and reduced noise. The signal processing circuit is implemented using a 65nm CMOS process, with a clock speed of 200MHz and power consumption of 50mW. The layered structure enables a 20% reduction in device size compared to conventional image pickup devices. The first and second structural bodies are connected using 10μm diameter through-vias spaced 20μm apart, with a total of 100 through-vias per device. External terminals include a 10-pin signal output terminal and a 5-pin power input terminal. The device operates on a 1.8V power supply, with a maximum operating temperature of 85°C.

Novelty and Inventive Step

The incorporation of an adaptive noise reduction module utilizing machine learning algorithms in the layered image pickup device is technically new and non-obvious compared to the source patent. The implementation of such a module requires careful consideration of signal processing, noise reduction, and real-time adjustment, making it a novel and inventive step beyond the original concept.

Alternative Embodiments and Variations

Alternative embodiments of the Enhanced Layered Image Pickup Device with Adaptive Signal Processing could include variations in the pixel array unit, such as different photodiode sizes or arrangements, or alternative machine learning algorithms for noise reduction. Additionally, the device could be implemented using different CMOS process sizes or clock speeds to optimize performance and power consumption.

Potential Commercial Applications and Market

The Enhanced Layered Image Pickup Device with Adaptive Signal Processing has significant commercial potential in industries such as smartphone manufacturing, digital photography, and surveillance systems, where high-quality image capture and processing are critical.

Field of Art

Image Sensor and Semiconductor Device Design, focusing on layered image pickup devices with integrated signal processing circuits, requiring expertise in CMOS imaging technologies, semiconductor packaging, and signal processing algorithms

Person of Ordinary Skill (PHOSITA) Profile

A skilled electrical engineer with a master's degree in electrical engineering or semiconductor design, experienced in image sensor architectures, familiar with CMOS fabrication processes, signal processing techniques, and machine learning applications in semiconductor design

Obviousness Rationale

A person having ordinary skill in the art would recognize that integrating an adaptive noise reduction module using machine learning into a layered image pickup device represents a predictable extension of existing image sensor design principles. The source patent's layered structural approach provides a clear framework for incorporating advanced signal processing capabilities. The technical variations disclosed in the PTD represent incremental improvements using known semiconductor design techniques and machine learning approaches commonly applied in image sensor technologies.

Obvious Combinations & Variations

Source Patent Element
Layered structural bodies with first body containing pixel array and second body containing signal processing circuits
PTD Variation
Adding an adaptive noise reduction module utilizing machine learning algorithms within the second structural body
Obviousness Reasoning
Integrating advanced signal processing modules into imaging device architectures is a known technique for improving image quality, and machine learning represents a predictable approach to noise reduction in semiconductor design
Source Patent Element
Through-via connections between structural bodies
PTD Variation
Implementing 10μm diameter through-vias spaced 20μm apart with 100 total connections
Obviousness Reasoning
Precise through-via design represents a routine optimization for semiconductor packaging, with specific dimensional choices being a matter of design preference and manufacturability
Source Patent Element
Image pickup device with lens module and color filter
PTD Variation
Adding real-time signal gain and offset adjustment using machine learning algorithms
Obviousness Reasoning
Dynamic signal processing techniques are well-known in imaging technologies, and applying machine learning to signal optimization represents an expected evolutionary design approach
Source Patent Element
Semiconductor device with signal processing circuits
PTD Variation
Implementing signal processing circuit using 65nm CMOS process with 200MHz clock speed
Obviousness Reasoning
Selection of specific semiconductor process nodes and clock speeds are standard design choices based on performance, power, and manufacturing considerations
35 U.S.C. § 103 Summary: Based on the teachings of US US12166060B2 and the published technical disclosure, a person having ordinary skill in the art would find the claimed variations of an adaptive noise reduction module, precise through-via implementation, and machine learning-based signal processing to be obvious extensions of prior art, rendering potential patent claims in this domain anticipated and non-patentable under 35 U.S.C. Section 103.

Original Patent Information

Patent NumberUS 121,660,602
TitleImage pickup device and electronic apparatus