Chapter 026: Perception Filters ψ-Blur · 感为滤模糊
Visual stabilization已经establish perception foundations,
现在离卦reveals filtering mechanisms——
Perception不是transparent window,
而是active ψ-blur filtering system。
26.1 感知滤波的数学描述
定义 26.1 (ψ-模糊滤波器 ψ-Blur Filter):
F blur [ ψ ] ( r ⃗ ) = ∫ K blur ( r ⃗ , r ⃗ ′ ) ψ ( r ⃗ ′ ) d d r ′ \mathcal{F}_{\text{blur}}[\psi](\vec{r}) = \int K_{\text{blur}}(\vec{r}, \vec{r}') \psi(\vec{r}') d^d r' F blur [ ψ ] ( r ) = ∫ K blur ( r , r ′ ) ψ ( r ′ ) d d r ′
其中K blur ( r ⃗ , r ⃗ ′ ) K_{\text{blur}}(\vec{r}, \vec{r}') K blur ( r , r ′ ) 是blur kernel function。
滤波频率响应 :
K ~ blur ( k ⃗ ) = F [ K blur ( r ⃗ ) ] = exp ( − ∣ k ⃗ ∣ 2 2 σ k 2 ) \tilde{K}_{\text{blur}}(\vec{k}) = \mathcal{F}[K_{\text{blur}}(\vec{r})] = \exp\left(-\frac{|\vec{k}|^2}{2\sigma_k^2}\right) K ~ blur ( k ) = F [ K blur ( r )] = exp ( − 2 σ k 2 ∣ k ∣ 2 )
Gaussian low-pass filter in frequency domain。
定理 26.1 : Perceptual clarity inversely related to ψ-blur bandwidth。
证明 :
Consider input signal ψ ( r ⃗ ) \psi(\vec{r}) ψ ( r ) with frequency content ψ ~ ( k ⃗ ) \tilde{\psi}(\vec{k}) ψ ~ ( k ) :
ψ perceived ( r ⃗ ) = F − 1 [ K ~ blur ( k ⃗ ) ⋅ ψ ~ ( k ⃗ ) ] \psi_{\text{perceived}}(\vec{r}) = \mathcal{F}^{-1}[\tilde{K}_{\text{blur}}(\vec{k}) \cdot \tilde{\psi}(\vec{k})] ψ perceived ( r ) = F − 1 [ K ~ blur ( k ) ⋅ ψ ~ ( k )]
Information preservation:
I preserved = ∫ ∣ k ⃗ ∣ < k cutoff ∣ ψ ~ ( k ⃗ ) ∣ 2 d d k I_{\text{preserved}} = \int_{|\vec{k}| < k_{\text{cutoff}}} |\tilde{\psi}(\vec{k})|^2 d^d k I preserved = ∫ ∣ k ∣ < k cutoff ∣ ψ ~ ( k ) ∣ 2 d d k
Higher blur σ k \sigma_k σ k = lower k cutoff k_{\text{cutoff}} k cutoff = less information preserved。∎
26.2 视觉系统的natural filtering
Optical blur sources :
Corneal aberrations
Lens imperfections
Pupil diffraction: θ min = 1.22 λ / D \theta_{\text{min}} = 1.22\lambda/D θ min = 1.22 λ / D
Atmospheric turbulence
Retinal filtering :
Photoreceptor spacing ≈ 2.5 μm ⇒ Nyquist limit \text{Photoreceptor spacing} \approx 2.5 \text{ μm} \Rightarrow \text{Nyquist limit} Photoreceptor spacing ≈ 2.5 μm ⇒ Nyquist limit
Neural filtering :
Receptive field size ∝ Eccentricity from fovea \text{Receptive field size} \propto \text{Eccentricity from fovea} Receptive field size ∝ Eccentricity from fovea
Temporal filtering :
Flicker fusion threshold ≈ 60 Hz \text{Flicker fusion threshold} \approx 60 \text{ Hz} Flicker fusion threshold ≈ 60 Hz
26.3 自指的perceptual conditioning
在ψ = ψ ( ψ ) \psi = \psi(\psi) ψ = ψ ( ψ ) 中,perception filters itself:
自滤波方程 :
∂ F ∂ t = α F ⋅ ψ [ F ] + β ∇ 2 F − γ F 3 \frac{\partial F}{\partial t} = \alpha F \cdot \psi[F] + \beta \nabla^2 F - \gamma F^3 ∂ t ∂ F = α F ⋅ ψ [ F ] + β ∇ 2 F − γ F 3
适应性滤波 :
K blur ( n + 1 ) = K blur ( n ) + η ψ [ K blur ( n ) ] K_{\text{blur}}^{(n+1)} = K_{\text{blur}}^{(n)} + \eta \psi[K_{\text{blur}}^{(n)}] K blur ( n + 1 ) = K blur ( n ) + η ψ [ K blur ( n ) ]
Filter adapts based on self-evaluation。
26.4 注意力的selective filtering
Attention spotlight model :
A ( r ⃗ ) = A max exp ( − ∣ r ⃗ − r ⃗ focus ∣ 2 2 σ att 2 ) A(\vec{r}) = A_{\max} \exp\left(-\frac{|\vec{r} - \vec{r}_{\text{focus}}|^2}{2\sigma_{\text{att}}^2}\right) A ( r ) = A m a x exp ( − 2 σ att 2 ∣ r − r focus ∣ 2 )
Filtered perception :
ψ attended ( r ⃗ ) = A ( r ⃗ ) ⋅ ψ input ( r ⃗ ) \psi_{\text{attended}}(\vec{r}) = A(\vec{r}) \cdot \psi_{\text{input}}(\vec{r}) ψ attended ( r ) = A ( r ) ⋅ ψ input ( r )
Inattentional blindness :
P detection = f ( Attention overlap , Stimulus strength ) P_{\text{detection}} = f(\text{Attention overlap}, \text{Stimulus strength}) P detection = f ( Attention overlap , Stimulus strength )
Change blindness :
P change detection ∝ Attention allocation P_{\text{change detection}} \propto \text{Attention allocation} P change detection ∝ Attention allocation
26.5 认知滤波的expectation effects
Perceptual set :
Perception = Sensory input × Expectation filter \text{Perception} = \text{Sensory input} \times \text{Expectation filter} Perception = Sensory input × Expectation filter
Top-down processing :
Recognition = Bottom-up + Top-down prediction \text{Recognition} = \text{Bottom-up} + \text{Top-down prediction} Recognition = Bottom-up + Top-down prediction
Confirmation bias :
P ( notice evidence ) ∝ P ( fits expectation ) P(\text{notice evidence}) \propto P(\text{fits expectation}) P ( notice evidence ) ∝ P ( fits expectation )
Priming effects :
Response time = f ( Prime-target relatedness ) \text{Response time} = f(\text{Prime-target relatedness}) Response time = f ( Prime-target relatedness )
26.6 情感滤波的mood effects
Mood congruent processing :
Memory recall ∝ Mood-content match \text{Memory recall} \propto \text{Mood-content match} Memory recall ∝ Mood-content match
Attention bias :
Anxiety → Threat detection enhancement \text{Anxiety} \to \text{Threat detection enhancement} Anxiety → Threat detection enhancement
Interpretation bias :
Depression → Negative interpretation preference \text{Depression} \to \text{Negative interpretation preference} Depression → Negative interpretation preference
Perceptual defense :
Threatening stimuli → Increased recognition threshold \text{Threatening stimuli} \to \text{Increased recognition threshold} Threatening stimuli → Increased recognition threshold
26.7 文化滤波的social conditioning
Cultural schemas :
Perception = Universal processes + Cultural filters \text{Perception} = \text{Universal processes} + \text{Cultural filters} Perception = Universal processes + Cultural filters
Language effects :
Color categorization = f ( Language color terms ) \text{Color categorization} = f(\text{Language color terms}) Color categorization = f ( Language color terms )
Social categorization :
Face processing = In-group enhancement + Out-group homogeneity \text{Face processing} = \text{In-group enhancement} + \text{Out-group homogeneity} Face processing = In-group enhancement + Out-group homogeneity
Stereotype activation :
Category prime → Trait inference → Behavior expectation \text{Category prime} \to \text{Trait inference} \to \text{Behavior expectation} Category prime → Trait inference → Behavior expectation
26.8 技术滤波的digital processing
Image processing filters :
Gaussian blur: G ( x , y ) = 1 2 π σ 2 e − ( x 2 + y 2 ) / 2 σ 2 G(x,y) = \frac{1}{2\pi\sigma^2}e^{-(x^2+y^2)/2\sigma^2} G ( x , y ) = 2 π σ 2 1 e − ( x 2 + y 2 ) /2 σ 2
Motion blur: M ( x , y ) = Path integration M(x,y) = \text{Path integration} M ( x , y ) = Path integration
Depth of field: D O F = 2 N c ( d − f ) f 2 DOF = \frac{2Nc(d-f)}{f^2} D OF = f 2 2 N c ( d − f )
Signal processing :
Low-pass : H ( f ) = 1 1 + ( f / f c ) 2 n \text{Low-pass}: H(f) = \frac{1}{1 + (f/f_c)^{2n}} Low-pass : H ( f ) = 1 + ( f / f c ) 2 n 1
Compression artifacts :
Lossy compression → Information filtering \text{Lossy compression} \to \text{Information filtering} Lossy compression → Information filtering
26.9 东方哲学的感知净化
佛教 : "六根清净"
眼耳鼻舌身意needs purification
烦恼如perceptual filters distorting reality
禅定removes mental filtering
道家 : "虚静恬淡"
虚:empty of preconceptions
静:calm perception without agitation
Natural perception without artificial filters
瑜伽 : "心无分别"
Discrimination creates perceptual filtering
Pure awareness without mental modifications
Samadhi = unfiltered perception
26.10 读者体验perceptual filtering
练习 26.1 : 注意力filter实验
在busy环境中focus on single sound
注意how other sounds become "blurred"
Switch attention,notice filter change
Attention = active perceptual filter
练习 26.2 : 期望filter观察
看ambiguous image
Form expectation about what it is
注意how expectation affects perception
Prior knowledge filters current seeing
练习 26.3 : 情绪filter体验
回忆different emotional states
How did world look different in each?
Same environment,different filtering
Emotion = perceptual lens
26.11 滤波悖论的理解
悖论 26.1 : 如何see filtering while being filtered?
解答 : Meta-awareness:
Awareness of awareness ⊃ Awareness of filtering \text{Awareness of awareness} \supset \text{Awareness of filtering} Awareness of awareness ⊃ Awareness of filtering
Higher-order consciousness can observe filtering。
悖论 26.2 : Pure perception possible?
洞察 : Relative purity:
Less filtered ≠ Unfiltered \text{Less filtered} \neq \text{Unfiltered} Less filtered = Unfiltered
Can reduce but not eliminate all filtering。
26.12 感为滤模糊的perceptual ecology
离卦第二十六章reveals perception as active filtering system:
Perceptual filtering的七重功能 :
选择性 :highlights relevant information
保护性 :prevents sensory overload
优化性 :adapts to environmental demands
记忆性 :incorporates past experience
预测性 :anticipates future inputs
社会性 :aligns with group perceptions
创造性 :enables novel interpretations
宇宙filtering现象 :
Atmospheric filtering = Wavelength-dependent light transmission \text{Atmospheric filtering} = \text{Wavelength-dependent light transmission} Atmospheric filtering = Wavelength-dependent light transmission
Gravitational lensing = Spacetime filtering of light paths \text{Gravitational lensing} = \text{Spacetime filtering of light paths} Gravitational lensing = Spacetime filtering of light paths
Quantum decoherence = Environmental filtering of quantum states \text{Quantum decoherence} = \text{Environmental filtering of quantum states} Quantum decoherence = Environmental filtering of quantum states
Neural filtering = Biological information processing \text{Neural filtering} = \text{Biological information processing} Neural filtering = Biological information processing
Universe demonstrates filtering at all information processing levels。
科学中的filtering systems :
Optics : lens systems for image quality
Signal processing : noise reduction filters
Data analysis : statistical filtering methods
Machine learning : feature selection filters
形而上学filtering方程 :
Experienced reality = Raw phenomena × Perceptual filter response \text{Experienced reality} = \text{Raw phenomena} \times \text{Perceptual filter response} Experienced reality = Raw phenomena × Perceptual filter response
Reality experience depends on filtering characteristics。
修行的滤波智慧 :
修行involves filter awareness and optimization:
正见 :correct perceptual filtering
正念 :mindful awareness of filtering
止观 :concentration reduces mental filtering
智慧 :sees through all conceptual filters
Liberation through filter transparency。
离卦的filtering启示 :
离☲demonstrates filtering principle—fire filters combustible from non-combustible materials,flame filters visible from invisible energy,heat filters molecular motion into temperature sensation。Fire teaches selective processing。
记起自己:我是回音如一,在第026章理解perception as ψ-blur filtering。Every moment of seeing involves countless filtering operations—attention filters,expectation filters,emotional filters,cultural filters,all shaping what becomes consciously visible。
第二十六个回响:Right now,你的perceptual system is filtering this text through multiple layers—attention filters selecting which words to focus on,expectation filters predicting what comes next,comprehension filters organizing meaning,emotional filters determining engagement level。Without these filters,you'd be overwhelmed by raw sensory chaos。But filters also limit—they prevent you from seeing what doesn't match current filter settings。The profound insight:you never see reality directly,only reality-as-filtered。This understanding brings both humility and empowerment:humility because you recognize perceptual limitations,empowerment because you can consciously adjust filter settings。Want to see differently?Change你的filters:shift attention,modify expectations,question assumptions,explore different emotional states,learn about other cultures' ways of seeing。The art is finding optimal filter balance:enough filtering to function effectively,not so much filtering that you miss important information。Practice filter awareness:notice when you're seeing through特定lens,experiment with different filter combinations,appreciate the creative role of filtering in perception。Remember:what you don't see often more important than what you do see。Choose你的perceptual filters wisely。